I’ve been tempted to buy one and do “real dev work” on it just to show people it’s not this handicapped little machine.
I built multiple iOS apps and went through two start up acquisitions with my M1 MBA as my primary computer, as a developer. And the neo is better than the M1 MBA. I edited my 30-45 min long 4k race videos in FCP on that air just fine.
> I built multiple iOS apps and went through two start up acquisitions with my M1 MBA as my primary computer, as a developer. And the neo is better than the M1 MBA. I edited my 30-45 min long 4k race videos in FCP on that air just fine.
Before I was a professional software developer, I used a scrawny second-hand laptop with a Norwegian keyboard (I'm not Norwegian) because that was what I could afford: https://i.imgur.com/1NRIZrg.jpeg
This was the computer I was developing PHP backends on + jQuery frontends, and where I published a bunch of projects that eventually led to me getting my first software development job, in a startup, and discovering HN pretty much my first day on the job :)
The actual hardware you use seems to me like it matters the least, when it comes to actually being able to do things.
I still manage and develop my php/jquery saas product on a 2011 27" iMac running Linux Mint, with an SSD being the only upgrade. Runs better than most new windows machines. No complaints.
I switch between Thinkpad T420s and PineBook Pro for all the hobby work.
T420s has loose USB ports and the power socket is almost falling off, so I plan to replace it by a 5 years old T14 G2 in the coming months.
I can afford the latest MacBook, but I'd rather not generate more e-waste that there is, and more importantly I feel closer to my users, and my code is efficient and straight to the point.
My non-hobby laptop is an old cheap Dell from 5-6 years ago.
The best laptop I ever had was a maxed-out Thinkpad P7x, and it came with the most meaningless job ever.
I can only compare that job to the one at a unicorn that gave me the latest and greatest MacBook. Not only the job was meaningless, the whole industry made no sense to me.
I just spent vacation deciding not to bring a laptop, but to use my android phone (a galaxy s22) with a hdmi adapter and Bluetooth travel keyboard. Plugged it in to the TV in our accomodation and had a lot of fun.
Running neovim on termux was fine. Developing elixir was no problem, the test suite took 5s on my phone, and takes 1s on my laptop. Rust and cargo compiling was slow enough that I didn't really enjoy it though.
Meant that I could just pack up instantly and have an agent do review workflows while I was out and about as well in my pocket, and didn't really notice a big battery hit.
I was using a M1 Mac Mini and only 8GB of RAM on it to build iOS apps for maybe a year. It's absolutely doable, though it very noticeably gets a little less snappy when building projects. When building in Xcode and then switching to Firefox to browse for instance, I could tell it took slightly longer to switch tabs and YouTube playback would occasionally stutter if too much was happening.
I also was using an Intel MacBook Pro with 16GB at the time. Doing the same thing there was much smoother and snappier. On the whole, it actually made me want to just the laptop instead since it "felt" nicer. (This isn't measuring build times or anything like that, just snappiness of the OS.)
It's starting to show its age, but I've been using a 2019 MacBook Pro with the Intel chip and 16GB of memory. Still handles multiple terminal sessions with Claude Code and Codex simultaneously, building in Xcode, running Docker in the background, etc.
(Maybe the fans sometimes sound like they're a jet engine taking off…)
Finally just put an order in for a new 16" MBP M5 Max with 48GB memory only because it looks like they're going to stop supporting the Intel stuff this year and no more software updates. It'll probably be obsolete in six months with the rate things are going, but I've been averaging seven years between upgrades so it should be good!
Oh my. All I have to say is cherish the first week of your M* experience. :D When I got rid of my intel MBP (it was an i7) for my MBA it was astonishing how fast and smooth it was.
I agree. It was utterly ridiculous how noticeable the improvement was. I was doing z3 solving for ICFP contest the first couple weeks after getting the m1 air. And it was consistently smoking my teammates maxed out i7 MBP
Sort of, they have no "hands", LLMs can only respond that they want to execute a tool/command. So they do that a lot to: read files, search for things, compile projects, run tests, run other arbitrary commands, fetch stuff from the internet etc.
Obviously the LLM inference is super heavy, but the actual work / task at hand is being executed on the device.
I use a 2015 MacBook Pro all the time--like right now. It does have 16GB of memory. It's what sits on my dining room table where I do most of my writing/browsing and which I take for travel. I do have an Apple Silicon MacBook Pro in my office but my downstairs "office" is a lot lighter and airier.
I use a 2015 MacBook Pro all the time--like right now.
I have a 2010 MacBook Air that I still use when traveling.
The battery is completely shot, but it works fine when plugged in. And if I'm on the road, I don't use my computer until I get to the hotel anyway. And even then, it's just fine for e-mail, browsing, and even Photoshop.
I'm glad enough people got M1 MacBook Airs now that the broader sentiment within the commentariat is changing and people are pushing back on the dismissals.
8gb has ALWAYS been fine in Apple Silicon Mac OS. RAM usage on a fresh boot is a meaningless statistic (unused RAM is wasted RAM). And they're just plain capable!
I have an older 8GB MacBook Air. This is false. I routinely have Slack, Chrome, iTerm, Visual Studio Code, and more open on it. It’s fine.
Those apps don’t need every single byte of memory you see in Activity Monitor to be active in RAM all of the time. The OS swaps out unused parts to the very fast SSD. If you push it so far that active pages are constantly being swapped out as apps compete then you start to notice, but the threshold for that is a lot higher than HN comments seem to think.
It really isn't. It is a capable machine but modern software has made it a lemon. And that is the only reason apple sells it. So that whoever buys it needs to buy another one prematurely, generating another sale.
Everything from apple to modern software is rotten to its core.
I've been finding it hard to wean myself off the standalone app but another major reason to do so is opening threads in separate tabs. I find as soon as I'm involved in two or more conversations on there it's super easy to start losing track of things.
I’m sick to death of this. It’s so devoid from reality in 2026 that I see it as a lowest common denominator populist political catchphrase more than any legitimate contributor to any conversation. My min spec MacBook Pro from 6 years ago doesn’t flinch at this, and it barely flinches at a whole lot more.
Can we please just move on? Maybe get your hardware checked if you’re legitimately still having these issues.
I could have two browser windows open in the late 1990s. I have about a thousand times as much RAM now. So even with 10x more bloat in the pages, I should be able to open 200 tabs just fine.
I was doing Android development and Verilog synthesis on a mobile Nehalem i5 in 2020. That machine is still totally adequate for anything a "normal person" does with their computer, provided they have good tab hygeine. The reality is that (unless you play video games and/or you want local LLM inference) the demands people place on their computers haven't changed significantly in at least 10 years.
I just retired my m1 air to being a server this month. They’re very capable laptops. If the neo is even comparable in spec it’s excellent for the price
My m1 air with 1TB ssd and 16GB of ram is a little champion, I use it during travel to play indie games like Hades II or Slay the Spire, and it works really well, better than my Steam Deck which broke. The only issue it really has is when I try to plug it into my docking station it struggles mightily with 2 2K screens and a 4K screen, so I just use my desktop in that case.
I am jealous of my wife’s 13” M5 iPad Pro though, that oled screen is gorgeous, a wonder of modern engineering.
I setup a self hosted runner and then use that in my CI workflows. Then I disabled it from sleeping so it can clamshell forever and now it sits here in my living room silently workin' https://imgur.com/a/EaBICdo
And, presumably for a combination of the Mac build (and hardware) being of niche interest and sitting outside the standard Linux workflows so it's annoying to administer. And serving a money-making audience (iOS app devs) who have a revenue stream and see the extra CI cost as worth it.
I'm still doing iOS dev on my 2020 M1 MPB, and it's fine! I expect that if I change out its battery and apply new thermal paste it would run for another 6 years.
It would have been a better fit for me than the M4 Air, I literally use it only for typing and browsing, plus a could of Mac-only tools. Brilliant machine but complete overkill for me. It's almost tempting to switch just to get rid of the display notch.
Better in terms of raw specs. The original M1 Air also came with 8GB of RAM, and the A18 Pro in the Neo is faster than the version of the M1 that shipped in the base model Air
most dev workflows from pre 2021 can probably run just fine on a NEO - i think once you get into conductor / 8 terminals with claude code territory that’s where things start to slow down
i just got an m5 max with 128gb of ram specifically to run local llms
Claude Code still runs things on your local machine. So if you have some pretty expensive transpilation, or resolving dependency trees that needs musl recompilation, or doing something rust, you still need a reasonable ammount of local firepower. More so if you're running multiple instances of them.
The argument is misrepresented - I think it's about frustration and convenience, not achievability.
I developed some work that keeps tens of thousands of people alive every day on a $100 Acer netbook almost 15 years ago. The tools are always there, I don't think anyone thinks the work is actually impossible to do on a limited machine.
It’s fine to if you don’t have any memory hogging apps. But as soon as you fire up a couple demanding Docker containers you’ll feel the pain. 8GB isn’t so much RAM for some applications.
Why do you think people buying the cheapest MacBook
available will be running Docket? Do you commonly run Docker containers on the cheapest Windows laptop available? Why not?
> I’ve been tempted to buy one and do “real dev work” on it just to show people it’s not this handicapped little machine.
But... you can do the same exercise with a $350 windows thing. Everyone knows you can do "real dev work" on it, because "real dev work" isn't a performance case anymore, hasn't been for like a decade now, and anyone who says otherwise is just a snob wanting an excuse to expense a $4k designer fashion accessory.
IMHO the important questions to answer are business side: will this displace sales of $350 windows machines or not, and (critically) will it displace sales of $1.3k Airs?
HN always wants to talk about the technical stuff, but the technical stuff here isn't really interesting. The MacBook Neo is indeed the best laptop you can get for $6-700.
But that's a weird price point in the market right now, as it underperforms the $1k "business laptops" (to avoid cannibalizing Air sales) and sits well above the "value laptop" price range.
No, you can't do real work on a $350 windows machine. No way such a setup is suitable for anything beyond browsing a tab or two and connecting to servers using SSH.
And, the whole shittiness of the experience will even distract you attempting real work: the horrible touchpad, the bad screen, the forced windows updates when you trying to start the machine to do something urgent, ads in Windows, the lack of proper programmability of Windows (unless you use WSL).... Add the fact that the toy is likely to break in a year or two. These issue exist on far more expensive Windows machines, how much more a $350 machine.
Leaving Windows machines and OS behind for more than a decade has been a continuing breath of fresh air. I have several issues with the Apple devices and macOS (as I have with Linux too), but on the whole they are far better than Windows. The only good thing about Windows that I miss on Macs is the file explorer and window management, not sure why Apple stubbornly refuses to copy those.
A lot of $350-ish Windows machines also don’t have SSDs but instead eMMC storage, which is dog slow and will make modern SSD-mandatory Windows feel even more awful to use.
If Windows/Linux/x86 is non-negotiable and that’s your budget, I would never in a million years recommend anything brand new. This is when you go pick up a $350 used midrange ThinkPad on eBay. It won’t outperform a Neo in terms of CPU and battery life but I guarantee it’ll be a better experience than the garbage routinely sold at this price point.
> No, you can't do real work on a $350 windows machine.
Sigh. I mean, even absent the obvious answers[1], that's just wrong anyway. You're being a snob. Want to run WSL? Run WSL. Want to run vscode natively? Ditto. Put it on a cheap TV and run your graphical layout and 3D modelling work. I mean, obviously it does all that stuff. OBVIOUSLY, because that stuff is all cheap and easy.
All the complaining you're doing is about preference, not capability. You're being a snob. Which is hardly weird, we're all snobs about something.
But snobs aren't going to buy the Neo either. Again, the business question here is whether the $350 junk users can be convinced to be snobs for $600.
[1] "Put Linux on it", "All of your stuff is in the cloud anyway", "It's still a thousand times faster than the machine on which I did my best work", etc...
You mean that machine from 30 years ago that was running 30 year old software that has nothing in common with today’s development? And how well does Linux run on 4GB?
That's a 16G windows box which will happily run multiple VMs for whatever your deployment environment is, something the Neo is actually going to struggle with. The Jasper Lake CPU is indeed awfully slow, but again for routine "dev" tasks that's just not a limit.
You would obviously refuse out of taste, but if you were actually forced to use this machine to do your job... you absolutely could.
Kinda comparing apples to oranges. AWS was using EBS and not local instance storage. So you’re easily looking at another order of magnitude latency when transmitting data over the network versus a local pcie bus. That’s gonna be a huge factor in what I assume is a heavy random seek load.
I wrote a longer comment already (https://news.ycombinator.com/item?id=47352526) but looking at the hot run performance and making big hand wavy guesses, the performance difference might not be as big as you'd expect.
But AWS beat the laptop? And there's no cost to performance analysis? Yes AWS is overpriced but how do you make that conclusion from this specific article? Because network disks were slower than SSDs? AWS also has SSD instances with local storage.
I haven't tried the newer I7i and I8g instance types (the newest instances with local storage) for myself, but AWS claims "I7i instances offer up to 45TB of NVMe storage with up to 50% better real-time storage performance, up to 50% lower storage I/O latency, and up to 60% lower storage I/O latency variability compared to I4i instances."
I benchmarked I4i at ~2GB/s read, so let's say I7i gets 3GB/s. The Verge benchmarked the 256GB Neo at 1.7GB/s read, and I'd expect the 512GB SSD to be faster than that.
Of course, an application specific workload will have its own characteristics, but this has to be a win for a $700 device.
It's hard to find a comparable AWS instance, and any general comparison is meaningless because everybody is looking at different aspects of performance and convenience. The cheapest I* is $125/mo on-demand, $55/mo if you pay for three years up front, $30/mo if you can work with spot instances. i8g.large is 468GB NVMe, 16GB, 2 vCPUs (proper cores on graviton instances, Intel/AMD instance headline numbers include hyperthreading).
Yeah, this is really about how ludicrously overpriced big cloud is. I’ve got a first gen M1 Max and it destroys all but the largest cloud instances (that cost its entire current market value per month!), at least in compute. It’s a laptop! A decent bare metal server in a rack will destroy any laptop.
It’s staggering. Jaw dropping. Bandwidth is even worse, like 10000X markup.
Yet cloud is how we do things. There’s a generation or maybe two now of developers who know nothing but cloud SaaS.
I agree and disagree, the benefit with cloud is you "don't need to manage it", it scales automatically, redundancy, and automatic backups etc. I do think you are right; in the future there will be more infrastructure as code as cost pressures become more obvious.
The tooling — K8S with all its YAML, Terraform, Docker, cloud CLI tools, etc. — is pretty hideously ugly and complicated. I watch people struggle to beat it into shape just like they did with sysadmin automation tools like Puppet and Chef a decade or more ago. We have not removed complexity, only moved it.
The auto scaling thing is a half truth. It can do this if you deploy correctly but the zero downtime promise is only true maybe half the time. It also does this at greatly inflated cost.
Today you can scale with bare metal. Nobody except huge companies physically racks anymore. Companies like Hetzner and DataPacket have APIs to bring boxes up. There’s a delay, but you solve that by a bit of over provisioning. Very very few companies have work loads that are so bursty and irregular that they need full limitless up and down scaling. That’s one of those niche problems everyone thinks they have.
The uptime promise is false in my experience. Cloud goes down for cluster upgrades and any myriad other reasons just as often as self managed stuff. I’ve seen serious unplanned outages with cloud too. I don’t have hard numbers but I would definitely wager that if cloud is better for uptime at all it’s not enough of an improvement to justify that gigantic markup.
For what cloud charges I should, as the deploying user, receive five nines without having to think about it ever. It does not deliver that, and it makes me think about it a lot with all the complexity.
The only technical promise it makes good on, and it does do this well, is not losing data. They’ve clearly put more thought into that than any other aspect of the internal architecture. But there’s other ways to not lose data that don’t require you to pay a 10X markup on compute and a 10000X markup on transfer.
I think the real selling point of cloud is blame.
When cloud goes down, it’s not your fault. You can blame the cloud provider.
IT people like it, and it’s usually not their money anyway. Companies like it. They’re paying through the nose for the ability to tell the customer that the outage is Amazon’s fault.
Cloud took over during the ZIRP era anyway when money was infinite. If you have growth raise more. COGS doesn’t matter.
With cloud, what you're really paying for is flexibility and scalability. You might not need either for your applications. At some startups, we needed it. We sized clusters wrong, needed to scale up in hours. This is something we wouldn't ever be able to do with our own hardware without tons of lead time.
If your application won't ever require more resources than a single server or two, then you are better off looking at other alternatives.
When I teach, I use "big data" for data that won't fit in a single machine. "Small data" fits on a single machine in memory and medium data on disk.
Having said that duckDB is awesome. I recently ported a 20 year old Python app to modern Python. I made the backend swappable, polars or duckdb. Got a 40-80x speed improvement. Took 2 days.
The funny thing is that those days you can fit 64 TB of DDR5 in a single physical system (IBM Power Server), so almost all non data-lake-class data is "Small data".
I'm curious - what were you doing that polars was leaving a 40-80x speedup on the table? I've been happy with it's speed when held correctly, but it's certainly easy to hold it incorrectly and kill your perf if you're not careful
Polars is fastest when you avoid eager eval mid-pipeline. If you see a 40x gap it's often from calling .collect() inside a loop or applying Python UDFs row-wise.
Might be tangential but in my recent experience polars kept crashing the python server with OOM errors whenever I tried to stream data from and into large parquet files with some basic grouping and aggregation.
Claude suggested to just use DuckDB instead and indeed, it made short work of it.
Props for identifying the issue immediately, but armed with that knowledge, why not redo the benchmark on a different instance type that has local storage? E.g. why not try a `c8id.2xlarge` or `c8id.4xlarge` (which bracket the `c6a.4xlarge`'s cost)?
as a broke ecologist, this little computer can do everything I need in R and word and is a phenomenal build for the price. I'm really enjoying it thus far.
Do they make any promises about persistence of local NVMe after something like a full-region power outage yet?
Because if you can't do durable commit on a single-region cluster that will be just temporarily unavailable without loosing committed data if something like that happened, it's not quite there unless you still stream a WAL to storage that they do promise you will survive a full blackout of all zones that store (part of) the data.
Idk how an AWS region would respond to a power outage, but i have tested this in AWS Outpost, and there, if you power down a rack, then power it back again, the baremetal instances will not be recreated. (I was surprised as I was expecting the EC2 health check to terminate them, but it does not work like that.)
My understanding is that if you stop/start an instance, your local storage is gone (as the instance might even end up in a different host), but if you just reboot the instance, it should keep the local storage.
Worth noting the c8gd local NVMe is ephemeral so you'd need to pre-stage the data each run, but for a benchmark like this that's actually ideal since you avoid EBS cold-read artifacts entirely.
I suspect the Neo’s A-series chip wipes the floor with a Pi.
I’m really surprised just how competitive it was in their benchmark. I was expecting “sure it doesn’t compete but it works and you can use it”, not “it beat an Amazon instance, though not a really powerful one”.
The DuckDB team benchmarked with an r7i.16xlarge which uses EBS - that's the expected bottleneck. A fairer comparison would be an i4i or c8gd with local NVMe, where you'd likely see the laptop and cloud instance much closer in practice.
On a MacBook, one can download a data set, reboot, install updates, etc and still have the dataset. Those nice-ish AWS instances will wipe their local storage if they are stopped. Sure, one needs backups, but this is still annoying.
Also, at on-demand prices, three months of continuous usage of a single c8gd.2xlarge will pay for that MacBook Neo. The MacBook Neo has a larger SSD than the AWS instances. To be fair, the MacBook Neo has seriously nerfed external IO bandwidth, so the c8gd.2xlarge will outperform it in networking. That being said, I think that any other Mac in the current lineup will utterly smoke c8gd.2xlarge if you are willing to use Thunderbolt-connected network adapters.
Given how little power modern Macs use, a little closet full of Macs with a decent network switch will easily run on a single 20A circuit and will perform better than quite a few thousands of dollars per month of AWS products. Sadly, you’re kind of stuck on MacOS (which is not actually a fantastic server OS) and the management tools are poor. Oh, well.
the laptop is gonna have some local code, maybe a lot, but if I'm doing legitimate "big data" that data is living i the cloud somewhere, and the laptop is just my interface.
Funny just yesterday I almost bought one but got cold feet and opted for a low range MacBook with M5 chip. The Apple sales rep was not convinced it would be enough when i described using it for vibecoding and deploying so kind of talked me out of getting the Neo. I normally use a mix of LLMs, then connect to Github and do a one-click deploy on CreateOS. Do you think I over-reacted? The price of the Neo is SO attractive, a clean half price compared to what I got.
I think you’ll be quite a bit happier. Between the quality of life stuff like the ancient life sensor, the pure quality stuff like a better screen and speakers, and extra RAM so it lasts longer that seems like a good decision.
The Neo is neat and for someone who mostly does surfing and standard office work kind of stuff I suspect it’s a pretty great little laptop for way less than Apple usually charges.
But it’s not going to compete with an M5 anything.
Imho 8GB RAM for productivity can quickly be restrictive. I used an M1 with 8GB and my current Macbook is M2 with 16GB, and to me the difference feels bigger than 2x. It seems not everyone here feels that way, but I'd say there's a reason Apple bumped the base models to 16 and makes that exclusive to non-Neo models.
You could get a laptop with an Nvidia GPU, 16gb ram, 512 ssd... or a 'cheap' Macbook.
I totally understand if you need to compile for iphones. We need to make apps for the lower and middle class people that think a $40/mo cellphone is a status symbol. I get it.
But if you are not... why? I hate windows, but we have Fedora... and you get an Nvidia. Is it just a status symbol? And I have a hard time believing people who tell me stories about low power consumption, because no one had cared about that until Apple pretended people cared about it.
> And I have a hard time believing people who tell me stories about low power consumption, because no one had cared about that until Apple pretended people cared about it.
That’s because battery life was pretty mediocre across the board, with Apple occasionally squeaking out a bit of an upper hand on the Air. Most laptops were in the same boat, aside from gaming and workstation laptops but battery life has never been the point of those.
That changed dramatically with the M-series Macs. People didn’t start caring because Apple did, but because it meant no longer being tethered to a wall, being able to do a lot of outings without a brick or charger cable at all, and on extended trips being able to get by with a little phone charger instead of a the usual huge ungainly brick.
One of the primary objectives of a laptop is portability, and long battery life is an objective upgrade in that category. Not everybody needs it but for those who do it’s difficult to give up once you’ve had it.
EDIT: Another advantage of that higher efficiency is that MacBooks can run at full performance without being plugged in without it obliterating battery life. x86 laptops universally throttle when untethered and while this can be disabled, they burn through their batteries much more quickly.
I don't think anyone that dismisses this really understands this. I've never had a laptop that could for more than about 3-4 hours doing dev work, but in 2014 I could get 8 hours of dev time out of an Air, and I can do that now on my M1 Macbook Pro.
For someone who is actually out and about all the time, this is life changing.
If you just sit with your laptop tethered at your desk all day, they why would you ever care?
To be honest I never had Issues with Battery Life on my ThinkPad.
I've gotten out 10-12 hours with the 96Wh Battery and never felt the need for much more.
I think most people who are so wowed by Macs bought just a garbage Windows Machine (e.g. almost everything from Asus and Acer) before and then splurged the money for a nice one, so obviously it's so much better in comparison.
Is that under Windows or Linux? It’s not awful, but depending on usage a MacBook can do 16h+ with the same size battery, especially if put into low power mode, which is substantially better.
The smaller 13” Air also gets similar numbers despite its smaller battery, which is a big deal for people who don’t want to lug around a 15/16” laptop.
Maybe it's an excellent experience these days, but every time I've tried Linux on desktop over the past 25 years I get burned. Maybe it works for a while, then your NIC driver gets borked and you spend 2 days trying to get it working again. Or some update goes sideways and you lose the GUI, launching only into a terminal. It's always something. And laptops have even less common hardware than desktops.
On the other hand, every Mac I've used over the past 15 years has been bulletproof. It turns on, it works, it runs *nix. It's an invisible interface to getting work done.
That's kinda the point of the Mac though, you don't have to get the right distribution or deal with pedantry, you buy, take it home, open it and will run for 8-10 hours of work without charging. No distro issues.
FWIW I have had no issues on a thinkpad for past 10 years running standard linux distros. I think it may come down to a combo of os and particular mb/laptop which is pretty easy to find recommendations.
> And I have a hard time believing people who tell me stories about low power consumption, because no one had cared about that until Apple pretended people cared about it.
I haven't packed a charger for the day for 3 years. I can work in coffee shops or on the couch for over 6 hours without even thinking about charging. I'm sorry but if you haven't tried the M* macbooks you don't know what you're criticising.
You get a long-lasting device that's usually pleasant to use. User experience is harder to measure than specs, but at least for me, Macbooks are consistently better laptops than everything else I've used.
- A familiar interface (iPhone is the most popular OS in the US)
- Good enough speed and snappiness for the tasks they can't do on their phone
- Can walk into Costco or buy online at Amazon without having to hunt for deals or refurbs
- Is from a brand they are familiar with and has an association with quality.
- Is somewhere around $500-$800, the most common price range for laptops today
The MacBook Neo ticks all those boxes, and it comes in fun colors. It's the one you can walk into a store, buy, not really sweat the speeds and feeds and know you will have a pretty great experience with. I'm not sure why so many people are having a hard time understanding this.
Yeah, but then MacBook is going to run smoother and faster than the Windows one (and I don’t want to spend even one extra minute on dealing with drivers on Linux). There’re just objective benchmarks for that.
And MacBooks also have a better display and build quality. Like, touchpad is still hit or miss on any non-Apple device.
Have you just woken up from a coma or have you literally just refused to evolve your “haha iPhones suck!” talking points from 2009? Move on. Nobody is going to engage with this.
I’m not surprised that the people in your social circles don’t care about being able to use a portable computer outside of their bedrooms. I assure you that in the real world battery life is front of mind for a great many people.
I’d also suggest not leaning so heavily on “but you get Nvidia!” when the crux of your gripe seems to be about brand hype. You are chasing a brand. You clearly do not know the first thing about the GPU/AI capabilities of the computers that you seem to hate so much.
Where do I get a Laptop with a Nvidia GPU for 600$ ?
I'm right now in the Market for a new Laptop, because I need way more GPU Power than my T470 provides, and to be honest the MacBookPros are quite competitively priced compared to the P-ThinkPads with Nvidia Cards. (Both around 3000€)
They also finally offer a matte screen option
The only thing holding me back right now is the soldered SSD, RAM (and shitty Linux support).
It was quite nice being able to upgrade RAM, SSD and replace the Battery on it. Otherwise it wouldn't have lasted for 9 years
Those speeds on the Pro/Max are impressive though, more in line with Gen5 NVMe drives. Those have been available in desktops for some time but AFAIK the controllers are still much too hot and power hungry for laptops, so I think Apple's custom controller is actually the first to practically hit those speeds on mobile.
I’m guessing so many devs started out on 32gb MacBooks that the NEO seems underpowered. but it wasn’t too long ago that 8gb, 1500mb/sec IO & so many cores was an elite machine.
I did a lot of dev work on a glorified eePC Chromebook when my laptop was damaged. You don’t need a lot of ram to run a terminal.
I’m hoping NEO resets the baseline testing environment so developers get back to shipping software that doesn’t monopolize resources. “Plays nice with others” should be part of the software developer’s creed.
Trying DuckDB on lower-end Macbooks does show you dont need much muscle for moderate-size analytics. Long term it isnt cost-effective compared to budget laptops but its super simple for self-contained pipelines. The thing is 8GB RAM leaves you stuck once your data actually grows past the marketing demo.
Fantastic tear down. Thank you. Amazing for Apple. I hope this is the trend going forward but probably not. But still a gazillion screws? I just replaced the keyboard for my old hp elitebook with two screws.
It seems like they’re starting to learn the cost of being too integrated.
They’ve slowly been moving towards making it easier to repair individual broken parts. I’m very happy to see that a new keyboard doesn’t require replacing the entire top case. That was just crazy.
I agree I don’t think it’s going to be something people really do.
I just thought it was neat. It’s a phone chip, we’ve never been able to do stuff like this on an Apple phone chip before. No one was porting this to the iPhone to run there.
In my mind this is purely a curiosity article, and I like that.
I think the form factor is basically the same (maybe slightly thicker) as a Macbook Air. It's basically an Air with lower performance in most dimensions.
You'd be surprised. There are many of us analysts in the third world who are paid pennies and expected to build large-scale exec dashboards from nontrivial data - with no cloud support whatsoever. ETL has to be local from hundreds of GBs of csv dumps.
I think it's partly tongue in cheek, because when "big data" was over hyped, everyone claimed they were working with big data, or tried to sell expensive solutions for working with big data, and some reasonable minds spoke up and pointed out that a standard laptop could process more "big data" than people thought.
> For our first experiment, we used ClickBench, an analytical database benchmark. ClickBench has 43 queries that focus on aggregation and filtering operations. The operations run on a single wide table with 100M rows, which uses about 14 GB when serialized to Parquet and 75 GB when stored in CSV format.
Processing data that cannot be processed on a single machine is fundamentally a different problem than processing data that can be processed on a single machine. It's useful to have a term for that.
As you say, single machines can scale up incredibly far. That just means 16 TB datasets no longer demand big data solutions.
I get your point, but I don’t know if big data is the right term anymore.
Many people like to think they have big data, and you kinda have to agree with them if you want their money. At least in consulting.
Also you could go well beyond a 16TB dataset on a single machine. You assume that the whole uncompressed dataset has to fit in memory, but many workloads don’t need that.
How many people in the world have such big datasets to analyse within reasonable time?
I think the definition of big is smaller than that. Mine was "too big to fit on a maxed-out laptop", effectively >8TB. Our photo collection is bigger than that, it's not 'big data'.
Or one could define it as too big to fit on a single SSD/HDD, maybe >30TB. Still within the reach of a hobbyist, but too large to process in memory and needs special tools to work with. It doesn't have to be petabyte scale to need 'big data' tooling.
>Can I expect good performance from the MacBook Neo with Slack, Microsoft Office, and Google Chrome signed into Atlassian and a CRM, all running simultaneously?
No.
>Do I reject a world where all of the above is necessary to realize value from an entry-level MacBook?
I’ve been tempted to buy one and do “real dev work” on it just to show people it’s not this handicapped little machine.
I built multiple iOS apps and went through two start up acquisitions with my M1 MBA as my primary computer, as a developer. And the neo is better than the M1 MBA. I edited my 30-45 min long 4k race videos in FCP on that air just fine.
> I built multiple iOS apps and went through two start up acquisitions with my M1 MBA as my primary computer, as a developer. And the neo is better than the M1 MBA. I edited my 30-45 min long 4k race videos in FCP on that air just fine.
Before I was a professional software developer, I used a scrawny second-hand laptop with a Norwegian keyboard (I'm not Norwegian) because that was what I could afford: https://i.imgur.com/1NRIZrg.jpeg
This was the computer I was developing PHP backends on + jQuery frontends, and where I published a bunch of projects that eventually led to me getting my first software development job, in a startup, and discovering HN pretty much my first day on the job :)
The actual hardware you use seems to me like it matters the least, when it comes to actually being able to do things.
I still manage and develop my php/jquery saas product on a 2011 27" iMac running Linux Mint, with an SSD being the only upgrade. Runs better than most new windows machines. No complaints.
I switch between Thinkpad T420s and PineBook Pro for all the hobby work.
T420s has loose USB ports and the power socket is almost falling off, so I plan to replace it by a 5 years old T14 G2 in the coming months.
I can afford the latest MacBook, but I'd rather not generate more e-waste that there is, and more importantly I feel closer to my users, and my code is efficient and straight to the point.
My non-hobby laptop is an old cheap Dell from 5-6 years ago.
The best laptop I ever had was a maxed-out Thinkpad P7x, and it came with the most meaningless job ever.
I can only compare that job to the one at a unicorn that gave me the latest and greatest MacBook. Not only the job was meaningless, the whole industry made no sense to me.
I just spent vacation deciding not to bring a laptop, but to use my android phone (a galaxy s22) with a hdmi adapter and Bluetooth travel keyboard. Plugged it in to the TV in our accomodation and had a lot of fun.
Running neovim on termux was fine. Developing elixir was no problem, the test suite took 5s on my phone, and takes 1s on my laptop. Rust and cargo compiling was slow enough that I didn't really enjoy it though.
Meant that I could just pack up instantly and have an agent do review workflows while I was out and about as well in my pocket, and didn't really notice a big battery hit.
And nowadays we have Debian running in a VM on Android [1]
[1] https://www.zdnet.com/article/how-to-use-the-new-linux-termi...
I was using a M1 Mac Mini and only 8GB of RAM on it to build iOS apps for maybe a year. It's absolutely doable, though it very noticeably gets a little less snappy when building projects. When building in Xcode and then switching to Firefox to browse for instance, I could tell it took slightly longer to switch tabs and YouTube playback would occasionally stutter if too much was happening.
I also was using an Intel MacBook Pro with 16GB at the time. Doing the same thing there was much smoother and snappier. On the whole, it actually made me want to just the laptop instead since it "felt" nicer. (This isn't measuring build times or anything like that, just snappiness of the OS.)
It's starting to show its age, but I've been using a 2019 MacBook Pro with the Intel chip and 16GB of memory. Still handles multiple terminal sessions with Claude Code and Codex simultaneously, building in Xcode, running Docker in the background, etc.
(Maybe the fans sometimes sound like they're a jet engine taking off…)
Finally just put an order in for a new 16" MBP M5 Max with 48GB memory only because it looks like they're going to stop supporting the Intel stuff this year and no more software updates. It'll probably be obsolete in six months with the rate things are going, but I've been averaging seven years between upgrades so it should be good!
Oh my. All I have to say is cherish the first week of your M* experience. :D When I got rid of my intel MBP (it was an i7) for my MBA it was astonishing how fast and smooth it was.
So, the m5 with 48gb of ram will be amazing.
I agree. It was utterly ridiculous how noticeable the improvement was. I was doing z3 solving for ICFP contest the first couple weeks after getting the m1 air. And it was consistently smoking my teammates maxed out i7 MBP
Well, Claude Cod and Codex should be doing most of their heavy lifting in the cloud?
Sort of, they have no "hands", LLMs can only respond that they want to execute a tool/command. So they do that a lot to: read files, search for things, compile projects, run tests, run other arbitrary commands, fetch stuff from the internet etc.
Obviously the LLM inference is super heavy, but the actual work / task at hand is being executed on the device.
The AI part yes. But they also use quite inefficient rendering on the cli.
yeah I run Claude code on a 2013 Mac book air that refuses to die, I don't think it's very compute heavy.
I use a 2015 MacBook Pro all the time--like right now. It does have 16GB of memory. It's what sits on my dining room table where I do most of my writing/browsing and which I take for travel. I do have an Apple Silicon MacBook Pro in my office but my downstairs "office" is a lot lighter and airier.
I use a 2015 MacBook Pro all the time--like right now.
I have a 2010 MacBook Air that I still use when traveling.
The battery is completely shot, but it works fine when plugged in. And if I'm on the road, I don't use my computer until I get to the hotel anyway. And even then, it's just fine for e-mail, browsing, and even Photoshop.
Try running Teams on it though!
I'm glad enough people got M1 MacBook Airs now that the broader sentiment within the commentariat is changing and people are pushing back on the dismissals.
8gb has ALWAYS been fine in Apple Silicon Mac OS. RAM usage on a fresh boot is a meaningless statistic (unused RAM is wasted RAM). And they're just plain capable!
It will do real work fine. But slack and a browser will bring it to its knees.
I have an older 8GB MacBook Air. This is false. I routinely have Slack, Chrome, iTerm, Visual Studio Code, and more open on it. It’s fine.
Those apps don’t need every single byte of memory you see in Activity Monitor to be active in RAM all of the time. The OS swaps out unused parts to the very fast SSD. If you push it so far that active pages are constantly being swapped out as apps compete then you start to notice, but the threshold for that is a lot higher than HN comments seem to think.
It really isn't. It is a capable machine but modern software has made it a lemon. And that is the only reason apple sells it. So that whoever buys it needs to buy another one prematurely, generating another sale.
Everything from apple to modern software is rotten to its core.
Only if you insist on running the standalone slack app for some reason. Why run one instance of Chrome when you can pay for two?
I've been finding it hard to wean myself off the standalone app but another major reason to do so is opening threads in separate tabs. I find as soon as I'm involved in two or more conversations on there it's super easy to start losing track of things.
I’m sick to death of this. It’s so devoid from reality in 2026 that I see it as a lowest common denominator populist political catchphrase more than any legitimate contributor to any conversation. My min spec MacBook Pro from 6 years ago doesn’t flinch at this, and it barely flinches at a whole lot more.
Can we please just move on? Maybe get your hardware checked if you’re legitimately still having these issues.
Maybe if you have 100 browser tabs or something silly like that?
A couple YouTube tabs are enough if you leave them running for long enough. Just one YT browser process will easily take up 1-4GB sooner or later.
Or it won’t because Chrome and MacOS will know how much RAM is available and manage it effectively.
While I agree with your statement, I don't think judging one's way of working and using their computer was necessary.
I could have two browser windows open in the late 1990s. I have about a thousand times as much RAM now. So even with 10x more bloat in the pages, I should be able to open 200 tabs just fine.
You don’t have an 8GB Apple Silicon MacBook, so you? So why did you post?
I was doing Android development and Verilog synthesis on a mobile Nehalem i5 in 2020. That machine is still totally adequate for anything a "normal person" does with their computer, provided they have good tab hygeine. The reality is that (unless you play video games and/or you want local LLM inference) the demands people place on their computers haven't changed significantly in at least 10 years.
I just retired my m1 air to being a server this month. They’re very capable laptops. If the neo is even comparable in spec it’s excellent for the price
My m1 air with 1TB ssd and 16GB of ram is a little champion, I use it during travel to play indie games like Hades II or Slay the Spire, and it works really well, better than my Steam Deck which broke. The only issue it really has is when I try to plug it into my docking station it struggles mightily with 2 2K screens and a 4K screen, so I just use my desktop in that case.
I am jealous of my wife’s 13” M5 iPad Pro though, that oled screen is gorgeous, a wonder of modern engineering.
> [...] and it works really well, better than my Steam Deck which broke.
Well, the MacBook Air was also a lot more expensive than the Steam Deck?
The M1 also consumes more power.
I just bought a second hand M1 64GB as my main work laptop, haha. They definitely are capable laptops
Yeah! My M1 air is now my iOS build server since GH actions bill macOS mins at 10x the price.
How do you use M1 Air as iOS build server. Is 8G sufficient for only doing iOS builds? Do you connect to it remotely?
Couls you please describe your dev process.
It works out pretty okay for me, I do it since GH runners are very expensive and I have my own hardware so why not. https://docs.github.com/en/actions/concepts/runners/self-hos...
I setup a self hosted runner and then use that in my CI workflows. Then I disabled it from sleeping so it can clamshell forever and now it sits here in my living room silently workin' https://imgur.com/a/EaBICdo
why does GH actions bill macOS minis 10X?
Ah sorry minutes, they bill the most for macOS probably because of what a pain it is to scale it with apples EULA (I'm guessing) https://docs.github.com/en/billing/reference/actions-runner-...
Mins here being short for minutes, not minis.
And, presumably for a combination of the Mac build (and hardware) being of niche interest and sitting outside the standard Linux workflows so it's annoying to administer. And serving a money-making audience (iOS app devs) who have a revenue stream and see the extra CI cost as worth it.
What is a macOS mini…
Not “mini”, “mins” -> minutes.
I know it's not really related, but how did you manage to build two startups worth getting acquired in such a short period of time?
I'm still doing iOS dev on my 2020 M1 MPB, and it's fine! I expect that if I change out its battery and apply new thermal paste it would run for another 6 years.
Would say get one with a fan, my small react native app building/indexing in xcode takes several minutes on a 2020 M1 macbook air
But damn I like that design
It would have been a better fit for me than the M4 Air, I literally use it only for typing and browsing, plus a could of Mac-only tools. Brilliant machine but complete overkill for me. It's almost tempting to switch just to get rid of the display notch.
Can you say a little more about what you mean by "better"? How much faster is editing?
Better in terms of raw specs. The original M1 Air also came with 8GB of RAM, and the A18 Pro in the Neo is faster than the version of the M1 that shipped in the base model Air
most dev workflows from pre 2021 can probably run just fine on a NEO - i think once you get into conductor / 8 terminals with claude code territory that’s where things start to slow down
i just got an m5 max with 128gb of ram specifically to run local llms
Heh, I also upgraded to run local LLMs. As a tiny aside, codex does not burn resources like CC does.
Does Claude Code take up that many local resources? I thought the heavy lifting was in the cloud?
Claude Code still runs things on your local machine. So if you have some pretty expensive transpilation, or resolving dependency trees that needs musl recompilation, or doing something rust, you still need a reasonable ammount of local firepower. More so if you're running multiple instances of them.
The argument is misrepresented - I think it's about frustration and convenience, not achievability.
I developed some work that keeps tens of thousands of people alive every day on a $100 Acer netbook almost 15 years ago. The tools are always there, I don't think anyone thinks the work is actually impossible to do on a limited machine.
It’s fine to if you don’t have any memory hogging apps. But as soon as you fire up a couple demanding Docker containers you’ll feel the pain. 8GB isn’t so much RAM for some applications.
Why do you think people buying the cheapest MacBook available will be running Docket? Do you commonly run Docker containers on the cheapest Windows laptop available? Why not?
> I’ve been tempted to buy one and do “real dev work” on it just to show people it’s not this handicapped little machine.
But... you can do the same exercise with a $350 windows thing. Everyone knows you can do "real dev work" on it, because "real dev work" isn't a performance case anymore, hasn't been for like a decade now, and anyone who says otherwise is just a snob wanting an excuse to expense a $4k designer fashion accessory.
IMHO the important questions to answer are business side: will this displace sales of $350 windows machines or not, and (critically) will it displace sales of $1.3k Airs?
HN always wants to talk about the technical stuff, but the technical stuff here isn't really interesting. The MacBook Neo is indeed the best laptop you can get for $6-700.
But that's a weird price point in the market right now, as it underperforms the $1k "business laptops" (to avoid cannibalizing Air sales) and sits well above the "value laptop" price range.
No, you can't do real work on a $350 windows machine. No way such a setup is suitable for anything beyond browsing a tab or two and connecting to servers using SSH.
And, the whole shittiness of the experience will even distract you attempting real work: the horrible touchpad, the bad screen, the forced windows updates when you trying to start the machine to do something urgent, ads in Windows, the lack of proper programmability of Windows (unless you use WSL).... Add the fact that the toy is likely to break in a year or two. These issue exist on far more expensive Windows machines, how much more a $350 machine.
Leaving Windows machines and OS behind for more than a decade has been a continuing breath of fresh air. I have several issues with the Apple devices and macOS (as I have with Linux too), but on the whole they are far better than Windows. The only good thing about Windows that I miss on Macs is the file explorer and window management, not sure why Apple stubbornly refuses to copy those.
A lot of $350-ish Windows machines also don’t have SSDs but instead eMMC storage, which is dog slow and will make modern SSD-mandatory Windows feel even more awful to use.
If Windows/Linux/x86 is non-negotiable and that’s your budget, I would never in a million years recommend anything brand new. This is when you go pick up a $350 used midrange ThinkPad on eBay. It won’t outperform a Neo in terms of CPU and battery life but I guarantee it’ll be a better experience than the garbage routinely sold at this price point.
> No, you can't do real work on a $350 windows machine.
Sigh. I mean, even absent the obvious answers[1], that's just wrong anyway. You're being a snob. Want to run WSL? Run WSL. Want to run vscode natively? Ditto. Put it on a cheap TV and run your graphical layout and 3D modelling work. I mean, obviously it does all that stuff. OBVIOUSLY, because that stuff is all cheap and easy.
All the complaining you're doing is about preference, not capability. You're being a snob. Which is hardly weird, we're all snobs about something.
But snobs aren't going to buy the Neo either. Again, the business question here is whether the $350 junk users can be convinced to be snobs for $600.
[1] "Put Linux on it", "All of your stuff is in the cloud anyway", "It's still a thousand times faster than the machine on which I did my best work", etc...
You mean that machine from 30 years ago that was running 30 year old software that has nothing in common with today’s development? And how well does Linux run on 4GB?
So weird to see this kind of flaming more than a decade after it got stale and silly. I mean, yeah, kinda: a 64MB K6-300 was pretty great!
But as to the 4G quip, that's showing some ignorance of where the market is. The value segment is filled with devices like this: https://www.amazon.com/HP-Stream-BrightView-N4120-Graphics/d...
That's a 16G windows box which will happily run multiple VMs for whatever your deployment environment is, something the Neo is actually going to struggle with. The Jasper Lake CPU is indeed awfully slow, but again for routine "dev" tasks that's just not a limit.
You would obviously refuse out of taste, but if you were actually forced to use this machine to do your job... you absolutely could.
This is as much an indictment of AWS compute as it is anything else.
Kinda comparing apples to oranges. AWS was using EBS and not local instance storage. So you’re easily looking at another order of magnitude latency when transmitting data over the network versus a local pcie bus. That’s gonna be a huge factor in what I assume is a heavy random seek load.
I wrote a longer comment already (https://news.ycombinator.com/item?id=47352526) but looking at the hot run performance and making big hand wavy guesses, the performance difference might not be as big as you'd expect.
The article is literally saying the opposite. Quote:
> Here's the thing: if you are running Big Data workloads on your laptop every day, you probably shouldn't get the MacBook Neo.
> All that said, if you run DuckDB in the cloud and primarily use your laptop as a client, this is a great device
But AWS beat the laptop? And there's no cost to performance analysis? Yes AWS is overpriced but how do you make that conclusion from this specific article? Because network disks were slower than SSDs? AWS also has SSD instances with local storage.
I haven't tried the newer I7i and I8g instance types (the newest instances with local storage) for myself, but AWS claims "I7i instances offer up to 45TB of NVMe storage with up to 50% better real-time storage performance, up to 50% lower storage I/O latency, and up to 60% lower storage I/O latency variability compared to I4i instances."
I benchmarked I4i at ~2GB/s read, so let's say I7i gets 3GB/s. The Verge benchmarked the 256GB Neo at 1.7GB/s read, and I'd expect the 512GB SSD to be faster than that.
Of course, an application specific workload will have its own characteristics, but this has to be a win for a $700 device.
It's hard to find a comparable AWS instance, and any general comparison is meaningless because everybody is looking at different aspects of performance and convenience. The cheapest I* is $125/mo on-demand, $55/mo if you pay for three years up front, $30/mo if you can work with spot instances. i8g.large is 468GB NVMe, 16GB, 2 vCPUs (proper cores on graviton instances, Intel/AMD instance headline numbers include hyperthreading).
Yeah, this is really about how ludicrously overpriced big cloud is. I’ve got a first gen M1 Max and it destroys all but the largest cloud instances (that cost its entire current market value per month!), at least in compute. It’s a laptop! A decent bare metal server in a rack will destroy any laptop.
It’s staggering. Jaw dropping. Bandwidth is even worse, like 10000X markup.
Yet cloud is how we do things. There’s a generation or maybe two now of developers who know nothing but cloud SaaS.
I watched everyone fall for it in real time.
I agree and disagree, the benefit with cloud is you "don't need to manage it", it scales automatically, redundancy, and automatic backups etc. I do think you are right; in the future there will be more infrastructure as code as cost pressures become more obvious.
Those benefits are at least partly lies though.
The tooling — K8S with all its YAML, Terraform, Docker, cloud CLI tools, etc. — is pretty hideously ugly and complicated. I watch people struggle to beat it into shape just like they did with sysadmin automation tools like Puppet and Chef a decade or more ago. We have not removed complexity, only moved it.
The auto scaling thing is a half truth. It can do this if you deploy correctly but the zero downtime promise is only true maybe half the time. It also does this at greatly inflated cost.
Today you can scale with bare metal. Nobody except huge companies physically racks anymore. Companies like Hetzner and DataPacket have APIs to bring boxes up. There’s a delay, but you solve that by a bit of over provisioning. Very very few companies have work loads that are so bursty and irregular that they need full limitless up and down scaling. That’s one of those niche problems everyone thinks they have.
The uptime promise is false in my experience. Cloud goes down for cluster upgrades and any myriad other reasons just as often as self managed stuff. I’ve seen serious unplanned outages with cloud too. I don’t have hard numbers but I would definitely wager that if cloud is better for uptime at all it’s not enough of an improvement to justify that gigantic markup.
For what cloud charges I should, as the deploying user, receive five nines without having to think about it ever. It does not deliver that, and it makes me think about it a lot with all the complexity.
The only technical promise it makes good on, and it does do this well, is not losing data. They’ve clearly put more thought into that than any other aspect of the internal architecture. But there’s other ways to not lose data that don’t require you to pay a 10X markup on compute and a 10000X markup on transfer.
I think the real selling point of cloud is blame.
When cloud goes down, it’s not your fault. You can blame the cloud provider.
IT people like it, and it’s usually not their money anyway. Companies like it. They’re paying through the nose for the ability to tell the customer that the outage is Amazon’s fault.
Cloud took over during the ZIRP era anyway when money was infinite. If you have growth raise more. COGS doesn’t matter.
Maybe cloud is ZIRPslop.
Not all IaC is Kubernetes.
With cloud, what you're really paying for is flexibility and scalability. You might not need either for your applications. At some startups, we needed it. We sized clusters wrong, needed to scale up in hours. This is something we wouldn't ever be able to do with our own hardware without tons of lead time.
If your application won't ever require more resources than a single server or two, then you are better off looking at other alternatives.
Honestly I think the best path is hybrid with the cloud as DR and sudden load scaling.
When I teach, I use "big data" for data that won't fit in a single machine. "Small data" fits on a single machine in memory and medium data on disk.
Having said that duckDB is awesome. I recently ported a 20 year old Python app to modern Python. I made the backend swappable, polars or duckdb. Got a 40-80x speed improvement. Took 2 days.
The funny thing is that those days you can fit 64 TB of DDR5 in a single physical system (IBM Power Server), so almost all non data-lake-class data is "Small data".
I'm curious - what were you doing that polars was leaving a 40-80x speedup on the table? I've been happy with it's speed when held correctly, but it's certainly easy to hold it incorrectly and kill your perf if you're not careful
20 year old BI app. Columnar DBs weren't really a thing. (MonetDB was brand new but not super stable. I committed the SQLAlchemy interface to it.)
Polars is fastest when you avoid eager eval mid-pipeline. If you see a 40x gap it's often from calling .collect() inside a loop or applying Python UDFs row-wise.
App is now lazy!
Might be tangential but in my recent experience polars kept crashing the python server with OOM errors whenever I tried to stream data from and into large parquet files with some basic grouping and aggregation.
Claude suggested to just use DuckDB instead and indeed, it made short work of it.
> The cloud instances have network-attached disks
Props for identifying the issue immediately, but armed with that knowledge, why not redo the benchmark on a different instance type that has local storage? E.g. why not try a `c8id.2xlarge` or `c8id.4xlarge` (which bracket the `c6a.4xlarge`'s cost)?
as a broke ecologist, this little computer can do everything I need in R and word and is a phenomenal build for the price. I'm really enjoying it thus far.
How did you get one already? I thought they were just up for pre-order
Shipping started yesterday, meaning preorders would already have arrived then
Mine started shipping on 8 March to arrive on the 11 March release date.
yea, preordered.
I adore DuckDB.
Did a PoC on a AWS Lambda for data that was GZ'ed in a s3 bucket.
It was able to replace about 400 C# LoC with about 10 lines.
Amazing little bit of kit.
This is awesome.
I wish more companies would do showcases like this of what kind of load you can expect from commodity-ish hardware.
I think it’s relevant to first read [1] to see why they’re doing this. It’s basically done as a meme.
[1] https://motherduck.com/blog/big-data-is-dead/
> An alternate definition of Big Data is “when the cost of keeping data around is less than the cost of figuring out what to throw away.”
That couldn't be more accurate
I would have benchmarked with an instance that has local nvme, like c8gd.4xlarge.
Do they make any promises about persistence of local NVMe after something like a full-region power outage yet? Because if you can't do durable commit on a single-region cluster that will be just temporarily unavailable without loosing committed data if something like that happened, it's not quite there unless you still stream a WAL to storage that they do promise you will survive a full blackout of all zones that store (part of) the data.
Yes. They promise to wipe your data. That SLA has all the nines you can ask for as long as you measure it in the right direction :)
You already lose your data after instance restart so I think that full region outage is already out of question.
Idk how an AWS region would respond to a power outage, but i have tested this in AWS Outpost, and there, if you power down a rack, then power it back again, the baremetal instances will not be recreated. (I was surprised as I was expecting the EC2 health check to terminate them, but it does not work like that.) My understanding is that if you stop/start an instance, your local storage is gone (as the instance might even end up in a different host), but if you just reboot the instance, it should keep the local storage.
Worth noting the c8gd local NVMe is ephemeral so you'd need to pre-stage the data each run, but for a benchmark like this that's actually ideal since you avoid EBS cold-read artifacts entirely.
Would it not also work on a raspberry.
With I/O streaming and efficient transformation I do big data on my consumer PC and good old cheap HDDs just fine.
I suspect the Neo’s A-series chip wipes the floor with a Pi.
I’m really surprised just how competitive it was in their benchmark. I was expecting “sure it doesn’t compete but it works and you can use it”, not “it beat an Amazon instance, though not a really powerful one”.
IO on a raspi is pathetic. As packaged it’s 100 times slower , with a M.2 hat it’s still 5x slower
The DuckDB team benchmarked with an r7i.16xlarge which uses EBS - that's the expected bottleneck. A fairer comparison would be an i4i or c8gd with local NVMe, where you'd likely see the laptop and cloud instance much closer in practice.
On a MacBook, one can download a data set, reboot, install updates, etc and still have the dataset. Those nice-ish AWS instances will wipe their local storage if they are stopped. Sure, one needs backups, but this is still annoying.
Also, at on-demand prices, three months of continuous usage of a single c8gd.2xlarge will pay for that MacBook Neo. The MacBook Neo has a larger SSD than the AWS instances. To be fair, the MacBook Neo has seriously nerfed external IO bandwidth, so the c8gd.2xlarge will outperform it in networking. That being said, I think that any other Mac in the current lineup will utterly smoke c8gd.2xlarge if you are willing to use Thunderbolt-connected network adapters.
Given how little power modern Macs use, a little closet full of Macs with a decent network switch will easily run on a single 20A circuit and will perform better than quite a few thousands of dollars per month of AWS products. Sadly, you’re kind of stuck on MacOS (which is not actually a fantastic server OS) and the management tools are poor. Oh, well.
That's not Big Data. If you "need to process Big Data on the move" - what you need is a network.
aye.
the laptop is gonna have some local code, maybe a lot, but if I'm doing legitimate "big data" that data is living i the cloud somewhere, and the laptop is just my interface.
Funny just yesterday I almost bought one but got cold feet and opted for a low range MacBook with M5 chip. The Apple sales rep was not convinced it would be enough when i described using it for vibecoding and deploying so kind of talked me out of getting the Neo. I normally use a mix of LLMs, then connect to Github and do a one-click deploy on CreateOS. Do you think I over-reacted? The price of the Neo is SO attractive, a clean half price compared to what I got.
Why do you need an M5 to run Cursor and a browser? Your laptop isn't doing anything in your described workflow.
I think you’ll be quite a bit happier. Between the quality of life stuff like the ancient life sensor, the pure quality stuff like a better screen and speakers, and extra RAM so it lasts longer that seems like a good decision.
The Neo is neat and for someone who mostly does surfing and standard office work kind of stuff I suspect it’s a pretty great little laptop for way less than Apple usually charges.
But it’s not going to compete with an M5 anything.
Imho 8GB RAM for productivity can quickly be restrictive. I used an M1 with 8GB and my current Macbook is M2 with 16GB, and to me the difference feels bigger than 2x. It seems not everyone here feels that way, but I'd say there's a reason Apple bumped the base models to 16 and makes that exclusive to non-Neo models.
If you have doubts and you have the money, why worry about it?
You could get a laptop with an Nvidia GPU, 16gb ram, 512 ssd... or a 'cheap' Macbook.
I totally understand if you need to compile for iphones. We need to make apps for the lower and middle class people that think a $40/mo cellphone is a status symbol. I get it.
But if you are not... why? I hate windows, but we have Fedora... and you get an Nvidia. Is it just a status symbol? And I have a hard time believing people who tell me stories about low power consumption, because no one had cared about that until Apple pretended people cared about it.
> And I have a hard time believing people who tell me stories about low power consumption, because no one had cared about that until Apple pretended people cared about it.
That’s because battery life was pretty mediocre across the board, with Apple occasionally squeaking out a bit of an upper hand on the Air. Most laptops were in the same boat, aside from gaming and workstation laptops but battery life has never been the point of those.
That changed dramatically with the M-series Macs. People didn’t start caring because Apple did, but because it meant no longer being tethered to a wall, being able to do a lot of outings without a brick or charger cable at all, and on extended trips being able to get by with a little phone charger instead of a the usual huge ungainly brick.
One of the primary objectives of a laptop is portability, and long battery life is an objective upgrade in that category. Not everybody needs it but for those who do it’s difficult to give up once you’ve had it.
EDIT: Another advantage of that higher efficiency is that MacBooks can run at full performance without being plugged in without it obliterating battery life. x86 laptops universally throttle when untethered and while this can be disabled, they burn through their batteries much more quickly.
I don't think anyone that dismisses this really understands this. I've never had a laptop that could for more than about 3-4 hours doing dev work, but in 2014 I could get 8 hours of dev time out of an Air, and I can do that now on my M1 Macbook Pro.
For someone who is actually out and about all the time, this is life changing.
If you just sit with your laptop tethered at your desk all day, they why would you ever care?
To be honest I never had Issues with Battery Life on my ThinkPad. I've gotten out 10-12 hours with the 96Wh Battery and never felt the need for much more.
I think most people who are so wowed by Macs bought just a garbage Windows Machine (e.g. almost everything from Asus and Acer) before and then splurged the money for a nice one, so obviously it's so much better in comparison.
Is that under Windows or Linux? It’s not awful, but depending on usage a MacBook can do 16h+ with the same size battery, especially if put into low power mode, which is substantially better.
The smaller 13” Air also gets similar numbers despite its smaller battery, which is a big deal for people who don’t want to lug around a 15/16” laptop.
How heavy is that ThinkPad?
Maybe it's an excellent experience these days, but every time I've tried Linux on desktop over the past 25 years I get burned. Maybe it works for a while, then your NIC driver gets borked and you spend 2 days trying to get it working again. Or some update goes sideways and you lose the GUI, launching only into a terminal. It's always something. And laptops have even less common hardware than desktops.
On the other hand, every Mac I've used over the past 15 years has been bulletproof. It turns on, it works, it runs *nix. It's an invisible interface to getting work done.
I'd be willing to gamble that you used Debian-family. Debian is outdated linux. It is literally designed to be 2 years outdated upon release.
Use Fedora. Its up to date.
Note that Fedora is NOT Arch.
That's kinda the point of the Mac though, you don't have to get the right distribution or deal with pedantry, you buy, take it home, open it and will run for 8-10 hours of work without charging. No distro issues.
But then you dont get Nvidia, 16gb, or 512 SSD.
And all you needed to do was know Fedora is SOTA. Once you know that, you don't need to change.
FWIW I have had no issues on a thinkpad for past 10 years running standard linux distros. I think it may come down to a combo of os and particular mb/laptop which is pretty easy to find recommendations.
> And I have a hard time believing people who tell me stories about low power consumption, because no one had cared about that until Apple pretended people cared about it.
I haven't packed a charger for the day for 3 years. I can work in coffee shops or on the couch for over 6 hours without even thinking about charging. I'm sorry but if you haven't tried the M* macbooks you don't know what you're criticising.
You get a long-lasting device that's usually pleasant to use. User experience is harder to measure than specs, but at least for me, Macbooks are consistently better laptops than everything else I've used.
People want a laptop that has
- Great battery life
- Solid build quality
- A familiar interface (iPhone is the most popular OS in the US)
- Good enough speed and snappiness for the tasks they can't do on their phone
- Can walk into Costco or buy online at Amazon without having to hunt for deals or refurbs
- Is from a brand they are familiar with and has an association with quality.
- Is somewhere around $500-$800, the most common price range for laptops today
The MacBook Neo ticks all those boxes, and it comes in fun colors. It's the one you can walk into a store, buy, not really sweat the speeds and feeds and know you will have a pretty great experience with. I'm not sure why so many people are having a hard time understanding this.
People care about how long you can run in between charging. Low power consumption helps with that, even if you don't care about it directly.
Yeah, but then MacBook is going to run smoother and faster than the Windows one (and I don’t want to spend even one extra minute on dealing with drivers on Linux). There’re just objective benchmarks for that.
And MacBooks also have a better display and build quality. Like, touchpad is still hit or miss on any non-Apple device.
My work laptop is a common HP model from just a few years ago.
The screen is seriously ‘meh’, a massive upgrade from the previous HP model’s “you paid how much for this?”
Both have plastic cases that are fine but don’t feel tight/solid.
The keyboards are 80% and off center so there’s a numpad, which makes things hard to type for me.
The trackpads are fine. Which is way better than I was expecting.
Neither held a candle in speed or quality to my 16 GB M1 Air, and they are developer laptops, not $600 models.
I’m pretty sure I’d want a Neo over a $600 PC for non-developer work.
And the noise. Spin the fan up. Now down. Now up. Now down. Random spinning HD noises too (2nd disk I don’t use). Just to sit on the desktop.
Have you just woken up from a coma or have you literally just refused to evolve your “haha iPhones suck!” talking points from 2009? Move on. Nobody is going to engage with this.
I’m not surprised that the people in your social circles don’t care about being able to use a portable computer outside of their bedrooms. I assure you that in the real world battery life is front of mind for a great many people.
I’d also suggest not leaning so heavily on “but you get Nvidia!” when the crux of your gripe seems to be about brand hype. You are chasing a brand. You clearly do not know the first thing about the GPU/AI capabilities of the computers that you seem to hate so much.
Where do I get a Laptop with a Nvidia GPU for 600$ ?
I'm right now in the Market for a new Laptop, because I need way more GPU Power than my T470 provides, and to be honest the MacBookPros are quite competitively priced compared to the P-ThinkPads with Nvidia Cards. (Both around 3000€) They also finally offer a matte screen option
The only thing holding me back right now is the soldered SSD, RAM (and shitty Linux support).
It was quite nice being able to upgrade RAM, SSD and replace the Battery on it. Otherwise it wouldn't have lasted for 9 years
> You could get a laptop with an Nvidia GPU, 16gb ram, 512 ssd... or a 'cheap' Macbook.
That laptop won't have half the battery life the macbook does. It really all only boils down to the "handiness" of the device.
Which laptop is this, with good Linux support?
> compared to 3–5 GB/s
Their numbers are a bit outdated. M5 Macbook pro SSDs are literally 5x this speed. It's wild.
I'm seeing ~6GB/sec: https://www.tomshardware.com/laptops/macbooks/m5-macbook-pro...
That's decently fast but not especially remarkable, most Gen4 NVMe drives can hit 6-7GB/sec.
To be clear, that article is about the base m5, not the m5 pro or m5 max.
https://www.apple.com/newsroom/2026/03/apple-introduces-macb...
"The new MacBook Pro delivers up to 2x faster read/write performance compared to the previous generation reaching speeds of up to 14.5GB/s..."
OP did just say M5 (implying the base model)
Those speeds on the Pro/Max are impressive though, more in line with Gen5 NVMe drives. Those have been available in desktops for some time but AFAIK the controllers are still much too hot and power hungry for laptops, so I think Apple's custom controller is actually the first to practically hit those speeds on mobile.
Interesting. Do you have a link?
For the TPC-DS results it would also have been nice to show how the macbook neo compares to the AWS instances.
Or am I missing something?
“Big data” doesn’t have a 5gb memory cap.
I’m guessing so many devs started out on 32gb MacBooks that the NEO seems underpowered. but it wasn’t too long ago that 8gb, 1500mb/sec IO & so many cores was an elite machine.
I did a lot of dev work on a glorified eePC Chromebook when my laptop was damaged. You don’t need a lot of ram to run a terminal.
I’m hoping NEO resets the baseline testing environment so developers get back to shipping software that doesn’t monopolize resources. “Plays nice with others” should be part of the software developer’s creed.
> TL;DR: How does the latest entry-level MacBook perform on database workloads? We benchmarked it to find out.
That's not tldr, that's just subheader.
Thank you! I was going to say the same thing. It doesn’t give mr an overview at all
You're right! I pushed an updated TL;DR block.
That c8g.metal-48xl instance costs $7.63008 on demand[1], so for the price of the laptop, you could run queries on it for about ~90 hours.
:shrug: as to whether that makes the laptop or the giant instance the better place to do one's work…
[1] https://aws.amazon.com/ec2/pricing/on-demand/
If you can fit it on a thumb drive, it's not Big Data.
I'm interested by one (not for big data) but only 8 GB or RAM is kinda really sad.
My good old LG Gram (from 2017? 2015? don't even remember) already had 24 GB of RAM. That was 10 years ago.
A decade later I cannot see myself being a laptop with 1/3rd the mem.
Did your LG Gram cost $450 (to make for $600 in today's money) in 2015-17?
If it didn't, Apple has other laptops today with more RAM.
Queue the endless blog posts about running tech on the potato macbook and being stunned it’s functional with massive trade-offs. Groundbreaking stuff.
That usage is "Cue", not "queue".
Cue the queue of blogs! Trigger the formation of a line of posts to be published sequentially.
this has a phone CPU/memory
other test:
2025-09-08 : "Big Data on the Move: DuckDB on the Framework Laptop 13"
"TL;DR: We put DuckDB through its paces on a 12-core ultrabook with 128 GB RAM, running TPC-H queries up to SF10,000."
https://duckdb.org/2025/09/08/duckdb-on-the-framework-laptop...
Mind blown, if you need to handle "big" data on the move - the macbook neo is not the right choice. - Who would have guessed that outcome?
It occurs to me that there is near zero overlap between people who use a Macbook Neo and people who run DuckDB locally.
It would be a surprise if more than 0.1% of Macbook Neo users have even heard of DuckDB.
Which means that this article is probably just riding the hype.
Trying DuckDB on lower-end Macbooks does show you dont need much muscle for moderate-size analytics. Long term it isnt cost-effective compared to budget laptops but its super simple for self-contained pipelines. The thing is 8GB RAM leaves you stuck once your data actually grows past the marketing demo.
I think you completely missed the point.
People buy Macbook Neo because they "just need a laptop" or are budget conscious.
I imagine a student would get their hands wet with Postgre before looking at DuckDB or similar.
It would be a surprise if they do heavy workloads with DuckDB. In which case it's definitely worth investing in a more powerful computer.
Can’t give up and admit that 8GB of RAM is enough, can you?
That's an awesome idea to get a bricked MacBook Neo really fast because those idiots soldered the SSD inside
Apple has been soldering the SSD into MacBooks for over 10 years now, and most 10 year old MacBooks still have a working SSD.
Not if you're powerusing it like in the Article and relying heavily on Swap.
Also there are countless reports of bricked M1 8GB MacBook Airs that are bricked because the SSD used up it's write cycles
https://youtu.be/0qbrLiGY4Cg?si=mjKn2oLjqAb36hPU
That's not what the video insinuates.
Not sure about the ssd in particular but the neo is apparently pretty modular
https://www.youtube.com/watch?v=5k7Lv7f-5CQ
Fantastic tear down. Thank you. Amazing for Apple. I hope this is the trend going forward but probably not. But still a gazillion screws? I just replaced the keyboard for my old hp elitebook with two screws.
I don't care about a gazillion screws, if it's serviceable in the End.
If Apple would build their laptops serviceable like ThinkPads I would buy one today.
It seems like they’re starting to learn the cost of being too integrated.
They’ve slowly been moving towards making it easier to repair individual broken parts. I’m very happy to see that a new keyboard doesn’t require replacing the entire top case. That was just crazy.
Seems completely unnecessary, there is probably 0 overlap between people who buy a cheap MacBook and people running DuckDB locally
I agree I don’t think it’s going to be something people really do.
I just thought it was neat. It’s a phone chip, we’ve never been able to do stuff like this on an Apple phone chip before. No one was porting this to the iPhone to run there.
In my mind this is purely a curiosity article, and I like that.
I've used MacBook Airs as primary dev machines multiple times in my career (before Apple silicon, when Airs had truly shit performance).
There is always a trade-off of cost/convenience/power, and some folks are going to end up the the Neo end of the spectrum.
I love small form factors, and I am what youd call a professionel :P
I think the form factor is basically the same (maybe slightly thicker) as a Macbook Air. It's basically an Air with lower performance in most dimensions.
You'd be surprised. There are many of us analysts in the third world who are paid pennies and expected to build large-scale exec dashboards from nontrivial data - with no cloud support whatsoever. ETL has to be local from hundreds of GBs of csv dumps.
It’s necessary because the ignorant keep saying 8GB of RAM is a deal breaking limitation on the cheapest MacBook available.
Oh great, the term "big data" is back.
So my definition of big data was data so big it cannot be processed on a single machine in a reasonable amount of time.
I guess they’re using a different definition?
I think it's partly tongue in cheek, because when "big data" was over hyped, everyone claimed they were working with big data, or tried to sell expensive solutions for working with big data, and some reasonable minds spoke up and pointed out that a standard laptop could process more "big data" than people thought.
> For our first experiment, we used ClickBench, an analytical database benchmark. ClickBench has 43 queries that focus on aggregation and filtering operations. The operations run on a single wide table with 100M rows, which uses about 14 GB when serialized to Parquet and 75 GB when stored in CSV format.
very much so…
In my former life as a soulless consultant mid-level IT managers really liked to hear the 3 "V"s mentioned: Velocity, Volume, Variety
The V of Value is very important in some circles.
Computers got bigger and software got smarter.
You have phones that are faster than cloud VMs of the past. You can use bare metal servers with up to 344 cores and 16TB of ram.
I used to share your definition too, but I now say that if it doesn’t open in Microsoft Excel, it’s big data.
Processing data that cannot be processed on a single machine is fundamentally a different problem than processing data that can be processed on a single machine. It's useful to have a term for that.
As you say, single machines can scale up incredibly far. That just means 16 TB datasets no longer demand big data solutions.
I get your point, but I don’t know if big data is the right term anymore.
Many people like to think they have big data, and you kinda have to agree with them if you want their money. At least in consulting.
Also you could go well beyond a 16TB dataset on a single machine. You assume that the whole uncompressed dataset has to fit in memory, but many workloads don’t need that.
How many people in the world have such big datasets to analyse within reasonable time?
Some people say extreme data.
I think they are simply referring to analytical workloads.
“Your data isn’t big” is a good working definition of big data.
Google has big data. You are not google.
I think the definition of big is smaller than that. Mine was "too big to fit on a maxed-out laptop", effectively >8TB. Our photo collection is bigger than that, it's not 'big data'.
Or one could define it as too big to fit on a single SSD/HDD, maybe >30TB. Still within the reach of a hobbyist, but too large to process in memory and needs special tools to work with. It doesn't have to be petabyte scale to need 'big data' tooling.
>Can I expect good performance from the MacBook Neo with Slack, Microsoft Office, and Google Chrome signed into Atlassian and a CRM, all running simultaneously?
No.
>Do I reject a world where all of the above is necessary to realize value from an entry-level MacBook?
In theory, yes.