[cj]

I'm excited about this. The previous generation base model 15" Air was good enough for our company to make it the default computer for everyone. Previously we were giving out base model MBP's. And they're $1000 cheaper.

Today, the MBP is just way too powerful for anything other than specific use cases that need it.

[giwook]

Out of curiosity, what are some good use cases for a MBP now with the MBAs being so powerful?

I can think of things like 4K video editing or 3D rendering but as a software engineer is there anything we really need to spend the extra money on an MBP for?

I'm currently on a M1 Max but am seriously considering switching to an MBA in the next year or two.

[giobox]

The Apple Silicon fanless MBAs are great until you end up in a workload that causes the machine to thermal throttle. I tried to use an M4 MBA as primary development machine for a few months.

A lot of software dev workflows often require running some number of VMs and containers, if this is you the chances of hitting that thermal throttle are not insignificant. When throttling under load occurs it’s like the machine suddenly halves in performance. I was working with a mess of micro services in 10-12 containers and eventually it just got too frustrating.

I still think these MBAs are superb for most people. As much as I love a solid state fanless design, I will for now continue to buy Macs with active cooling for development work. It’s my default recommendation anytime friends or relatives ask me which computer to buy and I still have one for light personal use.

[davnicwil]

While I agree that the slowdown is very noticeable once the MBA gets hot to the touch, I joke that it's a feature, encouraging you to take a cooldown break every once in a while :-)

More seriously though I agree it depends on workload. If you've got a dev flow that hits the resources in spikes (like initial builds that then flatten off to incremental) it works pretty well with said occasional breaks but if your setup is just continuously hammering resources it would be less than ideal.

[dev_l1x_be]

It is just Apple’s way trying to tell you not to use microservices.

[philistine]

It's all related to things outside the CPU and GPU that made me choose a base model M5 Macbook Pro. I prefer the larger 14-inch screen for its 120hz capability and much better brightness and colour capability. I adore that there are USB-C ports on both sides for charging. The battery's bigger. That's about it.

[sgarland]

If nothing else, I’ve learned that for me personally, 14” is the sweet spot for a laptop. It’s just enough over the 13” to be good, without being obnoxiously large.

I also like NanoTexture way more than I thought I would, so there’s that.

[studmuffin650]

I’ve hit limitations of M1 Max pros all the time (generally memory and cpu speeds while compiling large c++ projects)

Airs are good for the general use case but some development (rust, C++) really eat cores and memory like nothing else.

[giwook]

What are your specs?

That does seem to fit the bill though of being more of a niche use case for which MBPs will be best suited for going forward.

Seems like most devs who are not on rust/c++ projects will be just fine with an Air equipped with enough memory.

[criemen]

> Out of curiosity, what are some good use cases for a MBP now with the MBAs being so powerful?

Local software development (node/TS). When opus-4.6-fast launched, it felt like some of the limiting factor in turnaround time moved from inference to the validation steps, i.e. execute tests, run linter, etc. Granted, that's with endpoint management slowing down I/O, and hopefully tsgo and some eslint replacement will speed things up significantly over there.

[schrijver]

The Macbook Pro has a HDMI port and a Micro SD slot, it’s great to not have to look for a dongle. Steep price difference though.

[aembleton]

Running a LLM locally on LM Studio. I find that that can tax my M4 Pro pretty well.

[robotresearcher]

It's a personal thing how much you care, but the speakers on the MBPs are pretty amazing. The Air sounds fine, even good for a notebook, but the MBPs are the best laptop speakers I have ever heard.

[jug]

Yes, back 10-15 years ago MBP felt more prosumer to me but they have monstrous performance and price points nowadays, like true luxury items or enterprise devices, that I'm happy to see good base specs on the MBA. The base spec on that device matters a lot. Also, Apple will probably release a cheaper MacBook this week and if the rumor holds, it'll be good enough for most consumers.

[windowsrookie]

The base 15" MacBook Pro was $2,399 10 years ago ($3,251.07 adjusted for Inflation) today it is $2,699.

https://everymac.com/systems/apple/macbook_pro/specs/macbook...

[boutell]

Because you can buy it with 32GB of unified RAM, the MBP is now actually the cheapest device for something... useful local AI models!

[drob518]

Have you used local AI models on a 32 GB MBP? I ask because I'm looking to finally upgrade my M1 Air, which I love, but which only has 16 GB RAM. I'm trying to figure out if I just want to bump to 32 GB with the M5 MBAir or make the jump all the way to 64 GB with the low-end M5 MBP. I love my M1 Air and I don't typically tax the CPU much, but I'm starting to look at running local models and for that I'd like faster and bigger. But that said, I don't want to overpay. Memory is my main issue right now. Anyway, if you have experience, I'd love to hear it. Which MBP, stats of the system, which AI model, how fast did it go, etc?

[rahimnathwani]

For local models are you wanting to do:

A) Embeddings.

B) Things like classification, structured outputs, image labelling etc.

C) Image generation.

D) LLM chatbot for answering questions, improving email drafts etc.

E) Agentic coding.

?

I have a MBP with M1 Max and 32GB RAM. I can run a 20GB mlx_vlm model like mlx-community/Qwen3.5-35B-A3B-4bit. But:

- it's not very fast

- the context window is small

- it's not useful for agentic coding

I asked "What was mary j blige's first album?" and it output 332 tokens (mostly reasoning) and the correct answer.

mlx_vlm reported:

  Prompt: 20 tokens @ 28.5 t/s | Generation: 332 tokens @ 56.0 t/s | Peak memory: 21.67 GB

[drob518]

Thanks for the info.

I’d like to do agentic coding first, but then chatbot and classification as lower priorities. I don’t really care about image gen.

Also, if you’re only able to run 35B models in 32GB, seems like I’d definitely want at least 64GB for the newer, larger models (qwen has a 122B model, right). My theory there is that models are only getting larger, though perhaps also more efficient.

[dev_l1x_be]

MPS is okish, is this is what you mean. ANE and CoreML is kind of meh for most use cases, great for some very specific tasks.

https://github.com/hollance/neural-engine/blob/master/docs/a...

[dillydogg]

I have noticed something similar. With the computer science undergrads and grad students I work with, Air is much more common than with the premeds and med students, many of whom have MBPs (who I am presuming do not need that much power).

[rocketvole]

I think its because compsci people know what they need to a greater degree than other majors. It's easier to upsell a computer to someone who doesn't really know about computers.

It could also be possible that compsci kids have a powerful desktop at home, or are more savvy with university cloud computing, for any edge cases or computationally expensive tasks.

[eru]

I use vscode's tunnel from my MacBook Air to my Archlinux desktop a lot.

The MacBook Air has ~16 GiB RAM. The Desktop has 128 GiB, and a lot more processing power and disk space.

[smelendez]

It’s possible that their departments give them computer recommendations that exceed what they actually need.

I’m not sure why this happens or who formulates these recommendations, but I’ve seen it before with students in fields that just don’t do much heavy duty computation or video editing being told to buy laptops with top-of-the-line specs.

[avhception]

I think there is a tendency to simply give in and buy bigger hardware if something doesn't work. With friends and family, I sometimes feel like having to talk them off the roof with regards to pulling the trigger on really expensive (relative to the tasks they're doing) hardware, simply because performance is often abysmal due to the fact that they trashed their OS with malware and bloatware and whatnot and can't understand all of that.

It's the same at work, to some degree. Our in-house ERP software performs like kicking a sack of rocks down a hill. I don't know how often I had to show devs that the hardware is actually idle and they're mostly derailing themselves with DB table locks, GC issues and whatnot. If I weren't pushing back, we probably would have bought the biggest VMs just to let them sit idle.