Buy the M5 Max 64 GB if you were buying it anyway.

The 16″ M5 Max at 40-core GPU + 64 GB unified memory is $4,499 through Apple’s configurator. It runs 35B-A3B MoE at 100+ tok/s via Ollama 0.21+ MLX silently; 70B dense Q4 fits with a sudo sysctl iogpu.wired_limit_mb tweak at 14–24 tok/s — workable for chat, and sustained 70B on battery will throttle. That’s the pitch — and it’s real. The counter-pitch is that the same $4,499 buys a 5090 + a much better dedicated AI box.

This is an editorial buyer’s guide. For the full specs + planner integration, see the M5 Max MacBook Pro 64 GB hardware card.

What it actually runs, measured

From our calibration table:

Qwen 3.5 27B dense, 6-bit MLX, 16K context — 686 PP / 20.3 TG tok/s. The honest dense-27B daily driver.
Qwen 3.5 122B-A10B, 4-bit MLX, 16K context — 1,239 PP / 60.6 TG tok/s. Tested on 128 GB; 64 GB users can’t fit this. This is what 128 GB Macs unlock.
30B-A3B MoE at Q4 — community reports 40–60 tok/s depending on prompt size. The sweet spot for 64 GB.

64 GB reality check: the 122B-class picks need 128 GB+ unified. On 64 GB you’re running 35B-A3B MoE comfortably, 70B dense Q4 with no headroom, and 27B dense with room to spare.

The prefill tax

Mac unified memory has lower effective bandwidth than discrete NVIDIA VRAM. For generation(producing tokens), this is fine — 20–60 tok/s feels fluent. For prefill (reading the prompt), it’s the honest friction.

A 32K-token prompt on the M5 Max takes 60–90 seconds before the first response token appears. On a 5090, the same prompt is 3–5 seconds. For long-context coding or long-document work, this delay is what people actually notice.

Short prompts (under 4K) feel native. Long prompts feel slow. Whether this matters depends entirely on what you use AI for.

Buy it if

You were buying an M5 Max anyway — for dev work, video editing, photo work, or because you live inside the Apple ecosystem. The 64 GB AI bonus is a real bonus.
Portability matters — you want local AI on battery, silent, at a coffee shop. No desktop rig touches this.
Most of your AI work is short-prompt interactive chat, coding assistance on recent files, lightweight docs. Prefill tax doesn’t bite.
You have a commercial license requirement and Apache/MIT model weights matter more than raw VRAM.

Don’t buy it if

You only want it for AI. $4,499 of NVIDIA gets you a 5090 + a capable host + peripherals with room left over. The 5090 will outperform on every axis except battery life and noise.
Image generation is your primary workload. FLUX.2-dev and HiDream-I1 pipelines run materially faster on CUDA than MLX — it’s not close.
You do long-context coding on 100K+ token codebases. The prefill latency compounds.
You’re tempted by the 128 GB configuration. 128 GB is currently pulled from Apple’s intake (as of April 11, 2026, memory-chip supply). Consider the Mac Studio M4 Max 64 GB at $3,199 instead if you don’t need portability.

The M5 refresh question

M5-series MacBook Pro landed March 2026. Between now and the M6 cycle (late 2026 / early 2027), no further material AI-relevant improvement is expected on the laptop line. Buying an M5 Max 64 GB today locks you in for ~18 months, which is fine. The M5 Mac Studio refresh slipped to October 2026 (Bloomberg/Gurman, April 19) — supply chain. If you want a desktop Mac, the wait just got longer; the buy-now case for M4 Max is correspondingly stronger.

Next step

Read the full M5 Max hardware card→