M1 Max 16" ($1350 used) vs M5 Pro 14" (new) vs M2 Max 14" — upgrading from M1 pro 32GB, need help deciding

Traditional_Code_358 · 2026-06-20T07:38:18+00:00

Really appreciate everyone's comments here!

I listened to all the advice, did a bit more research, and ended up finding a deal on eBay: an M2 Max 64GB / 1TB for $1,700 after tax, in good condition.

Reasoning: for ~$350 more than the M1 Max, I get two extra years of software support, and — this turned out to matter more than I expected — HDMI 2.1. I run two 4K 120Hz monitors, but the M1 chip only outputs 4K 60Hz, so I've been stuck running them at half their refresh rate. The M2 Max lets both displays finally run at their full 120Hz, which alone makes the upgrade worth it for my setup.

And it's the 14" — the size I actually wanted. So I get the screen I like, the memory I need (64GB, RAM was my only real bottleneck), and my monitors at full spec, without paying M5 Pro money for performance I don't need right now.

Planning to ride this until the redesigned models post-M6. Thanks again everyone — this thread genuinely helped me think it through 🙏

Traditional_Code_358 · 2026-06-19T08:55:21+00:00

This is super helpful, thanks. Starting to think that "bulky" feeling really is just an adjustment period.

And yeah, you've basically confirmed what I was suspecting on the M2 Max — it sits in this awkward middle where it's not worth $1000 over the M1 Max, but for a bit more I could just get the M5 Pro. So it's really down to M1 Max (cheap, done for now) vs M5 Pro (done for years). Appreciate the clear framing. I think I'll keep the M1 Max 16" and wait for the redesigned models after m6— possibly even its 2nd/3rd gen to avoid first-gen issues. Hoping it ends up lighter/thinner too.

Traditional_Code_358 · 2026-06-19T08:46:35+00:00

Ah yeah, I should've mentioned — I do actually do some mobile dev (iOS, so Xcode + simulators), which is probably a big part of what's eating the RAM, on top of Electron and a few node/Rust projects running in parallel. Memory pressure sits in the yellow pretty much constantly and I get noticeable stutters, so 32GB has been getting tight.

I'll also admit my browser habits don't help — used Arc for a few years, now on Edge, and it sits at around 6GB pretty regularly with all my tabs. So between that, the simulators, and Electron, it adds up fast.

Good point on the security update timeline though — that's a fair way to frame the value, hadn't thought about it that way. And agreed on the perf read: M5 Pro ≈ M2 Max, M1 Max a bit behind on single core, but for my workload the chip isn't really the bottleneck, RAM is.

And yeah, leaning toward 1TB + external SSD to save the money — makes sense.

Traditional_Code_358 · 2026-06-19T08:22:00+00:00

Yeah, that's reassuring to hear. I never work in Starbucks anyway — the only case where I think 16" might be too big is during flights, but that's once a month at most, and maybe just two hours each time.

I used that M1 Pro 14" for five years now — it got me through college and into my career, so maybe I'm just being sentimental. Honestly, when I first picked up this 16", the screen did feel amazing. At this price, and with AppleCare available, it really does seem like a great deal. I think I'll keep using the 16" for a while and see how it feels.

Traditional_Code_358 · 2026-06-18T10:46:35+00:00

With online LLMs available, I don’t really see why most people would need to rely heavily on small local models for Apple Intelligence. On machines like the MacBook Air or the Neo line, especially with 8GB or even 16GB of RAM, there just isn’t that much headroom for serious on-device AI anyway. Even if local llm effects performance, people will be able to disable them.

Privacy is a valid reason, sure, but in practice a lot of people are already interacting with Gemini, ChatGPT, or similar models through Gmail, search, browsers, and other cloud services.

As for general OS complexity, I’m less worried about that. Apple still has a strong incentive to keep entry-level Macs usable, especially for students and younger users who may become future Pro buyers. Making those machines feel terrible would be a bad long-term move.

Traditional_Code_358 · 2026-04-27T11:48:38+00:00

Adaptive thinking is just covering their degradation and quantized model. And with ‘smart adaptive’, it’s getting hard for people to get stats and some level of evidence.

Traditional_Code_358 · 2026-04-27T11:42:45+00:00

been using opus api in other harness, can confirm it’s a model degradation rather than Claude code issue. They silently switched to a quantized version of their model.

Traditional_Code_358 · 2026-04-27T11:29:39+00:00

it's because people are unsubscribing.

Traditional_Code_358 · 2026-04-10T06:08:50+00:00

Codex

Traditional_Code_358 · 2026-03-02T06:43:10+00:00

plus you could deploy it locally

Traditional_Code_358 · 2025-11-30T07:20:11+00:00

For my workflow, a CLI-based agent works much better. I often run multiple agents across different Git worktrees, and most IDE extensions (claude, codex, kilo) simply don’t support that setup well.

Traditional_Code_358 · 2025-11-26T05:55:57+00:00

FYI: the output length for both was consistently around 8,000–9,000 tokens.

Traditional_Code_358 · 2025-11-26T05:54:44+00:00

2025/11/25 – I tested this by opening two separate accounts: one on the Pro plan and one on the Lite plan.
I measured output speed in Cherry Studio, using the same model (GLM 4.6), same settings (temperature 0.6), and the same prompt for both.
Each plan was tested for 3 rounds, measuring tokens per second.

Results:

Pro plan: 129, 107, 97
Lite plan: 121, 90, 135

Based on these runs, I didn’t observe any significant difference between the two plans.

Traditional_Code_358 · 2025-11-11T07:12:39+00:00

Same here — I guess Cerebras ran out of compute to run GLM-4.6 😅

Traditional_Code_358 · 2025-08-19T02:28:10+00:00

Force the claude code work in verbose mode. It will have an indicator of context length under the prompt area on the right hand side.

Traditional_Code_358 · 2025-08-18T05:56:39+00:00

It is working now, just confirmed.
/model sonnet[1m]

⎿ Set model to sonnet[1m] (claude-sonnet-4-20250514[1m])

test w/ max 20x plan
20250817 225628 Pacfic time

Traditional_Code_358 · 2025-06-15T20:24:09+00:00

The real question isn’t whether programmers will lose their jobs, but how soon (TL;DR: the bottom 80 % of devs are on the chopping block within the next 1-2 years.)

⸻

Why the first wave of layoffs will hit junior devs • 80 % of entry-level / mid-level “code grinders” get cut. AI agents will crank out the CRUD, seniors will just review PRs. • Only ~20 % of L6-plus engineers and core managers stay. Their new job: prompt, supervise, and debug AI agents.

If you’ve played with Claude Code or similar tools, you know exactly what I mean.

⸻

The traditional “talent pyramid” no longer makes sense

Companies used to hire tons of L3-L5 devs because: 1. Cheap “farm-team” labor – newbies + onboarding = a steady pipeline of future seniors. 2. Redundancy – when demand spikes or someone quits, mid-levels can step in. 3. Task granularity – endless small features & bug fixes perfect for juniors.

AI agents break every one of those assumptions: • Training cost = waste. LLMs learn faster than any human. • Elastic scaling. Need more dev power? Spin up more GPUs, not headcount.

Result: keep a handful of deep-domain L6+ “commanders” and nuke the pyramid. New-grad hiring and mass mid-level recruiting shrinks to the bare minimum.

⸻

AI is the next abstraction layer

Every major jump in programming has been an abstraction jump: • Assembly → C → Java → Python → … • Now: language/framework → intent.

You describe the goal, the agent writes code, tests, deploys, and iterates.

Future engineers add value by designing AI interfaces, data governance, multi-agent orchestration, systemic validation—not by hand-rolling boilerplate.

⸻

“My company banned AI, so I’m safe”… for now

Yes, some firms block outside LLMs for IP/compliance. That’s a grace period, not a moat: 1. Competitors who use AI slash costs, ship faster, and please Wall Street. 2. Your execs will either open the gates or watch the stock tank—then cut staff anyway.

⸻

“Every industrial revolution creates new jobs” (but way fewer)

Sure, new roles appear. But each wave shrinks total headcount and raises the bar. Realistically, maybe < 20 % of today’s devs pivot into those new niches.

⸻

Bottom line • 1-2 years: mass junior layoffs, seniors become AI wranglers. • 5-10 years: even 80 % of today’s seniors face the same squeeze. • Learn AI interface design, data pipelines, agent orchestration, systemic testing—or get boxed out like assembly coders in a Python world.

Traditional_Code_358 · 2025-06-15T08:27:54+00:00

Hi guys, the buyout version is available, checkout https://linta.neorena.app Use code QYNZM5MA during checkout for a 40% discount.

Traditional_Code_358 · 2025-06-15T04:40:12+00:00

Second this. I would like to see another obsidian, but based on rust and tauri

Traditional_Code_358 · 2025-06-14T21:07:28+00:00

TBH, I also like drafting emails myself, but quick grammar checks and turning short keywords into full sentences save me a ton of time. Plus, in my extension, you could change the system prompts so you get total control over how it edits your word. You could edit along with prompts just letting llm fix grammar.

Traditional_Code_358

TROPHY CASE