How fast is the M5 Max for local LLMs?

Published March 2026 benchmarks on the M5 Max 128GB (18-core CPU, 40-core GPU, 614 GB/s) show gpt-oss 120B at Q8 generating 88 tok/s at 4K context and 64 tok/s at 32K, Qwen3.5-122B-A10B 4-bit at 55-66 tok/s, and Qwen3-Coder-Next 8-bit at 48-79 tok/s depending on context. Prompt processing reaches 2,700+ tok/s on gpt-oss 120B at 16K context. These are MoE models — dense models run much slower at the same size.

Should I upgrade from an M4 Max to an M5 Max for local AI?

No, not for inference alone. The M5 Max's 614 GB/s is 12% more bandwidth than the M4 Max's 546 GB/s, which translates to roughly a 19-27% token-generation improvement — noticeable, not transformative. Both chips run the same models at the same quants. Buy the M5 Max if you are buying a new machine anyway; keep the M4 Max if you own one.

Is the M5 Pro good enough for local LLMs?

For small and mid models, yes; for this site's typical workloads, it is the wrong buy. Both M5 Pro memory configs (24GB and 48GB) run at 307 GB/s — half the M5 Max's 614 GB/s — so the same model generates tokens at roughly half speed. The M5 Pro 48GB fits a 70B Q4 but decodes it slowly. If local AI is a primary use, the jump to an M5 Max is the single most valuable line item in the configurator.

How much does the M5 Max MacBook Pro cost in 2026?

As of August 2026: 16-inch M5 Max 36GB from about $3,899-3,999 ($3,599 for the 14-inch on current deals), 48GB/2TB around $4,399 with discounts, and the 128GB/2TB config at $6,899-6,999. These prices have been rising, not falling — Apple repriced the lineup during the 2026 memory shortage.

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Hardware August 13, 2026

M5 Max MacBook Pro for Local LLMs: What 614 GB/s Actually Buys You

The M5 Max raises unified memory bandwidth to 614 GB/s. That is a 12% bump over the M4 Max — real, but the benchmark numbers going around imply much more, and the difference is worth understanding before you spend $4,399 to $6,999.

Planning an OpenClaw setup around Apple Silicon?

See our AI training options. We'll match the chip and memory config to your model list before you spend anything.

Bottom Line (August 2026)

M5 Max = 614 GB/s, up 12% from the M4 Max’s 546 GB/s. Expect roughly 19-27% faster token generation, not a generational leap.
The real M5 story is prompt processing — 2,700+ tok/s on gpt-oss 120B at 16K context. Agents that ingest big files feel this more than the decode bump.
Skip the M5 Pro for local AI: both its configs run at 307 GB/s — half the Max. Memory capacity is not the only spec that matters.
M4 Max owners should not upgrade. Buying new? The M5 Max is the best laptop chip for local inference, full stop.
Prices (Aug 2026): 16” 36GB ~$3,899-3,999 · 48GB/2TB ~$4,399 · 128GB/2TB $6,899-6,999. Rising, not falling.

The Benchmarks, With the Context They Need

Published M5 Max 128GB numbers (hardware-corner.net, March 2026; 18-core CPU / 40-core GPU):

Model	Quant / size	4K ctx	16K ctx	32K ctx
gpt-oss 120B	Q8, 64GB	87.9 tok/s	76.0	64.5
Qwen3.5-122B-A10B	4-bit, 69.6GB	65.9 tok/s	60.6	54.9
Qwen3-Coder-Next	8-bit, 84.7GB	79.3 tok/s	74.3	68.6 (48.2 @ 64K)
Qwen3.5-27B (dense)	6-bit, 26GB	23.6 tok/s	20.3	14.9

Read the last row before you get excited. A dense 27B runs at 23.6 tok/s while a 122B MoE runs at 65.9. The eye-popping numbers on this chip come from sparse MoE architecture — models that read only a few billion active parameters per token — not from the silicon alone. If someone quotes you “88 tok/s on a 120B model” as evidence the M5 Max is four times faster than an M4 Max, they are comparing architectures and runtimes, not chips. Chip-to-chip, the honest expectation is the bandwidth math: +12% bandwidth, roughly 19-27% more generation speed.

The number that did jump generationally is prefill: 1,325-2,710 tok/s prompt processing on gpt-oss 120B. For agentic use — pasting a repo, re-reading a long transcript every turn — prefill is most of your wait, and this is where the M5 Max pulls clearly ahead.

M5 Pro vs M5 Max: the Half-Bandwidth Trap

Apple’s configurator makes the M5 Pro 48GB look like the sensible middle. For local AI it is not, and the reason is one line in the tech specs: the M5 Pro runs 307 GB/s at both 24GB and 48GB. Same model, same quant, roughly half the tokens per second of a Max. Generation speed on Apple Silicon tracks memory bandwidth almost linearly, because decode is memory-bound — the mechanism our why is my local LLM slow page walks through.

The configurator decision, ranked by what you get per dollar for inference:

M5 Max 48GB (~$4,399 as of Aug 2026) — every current agentic MoE (Laguna XS at Q8, gpt-oss 20B, Qwen 3.6 27B at Q8) plus 70B Q4, at full 614 GB/s.
M5 Max 128GB ($6,899-6,999) — adds gpt-oss 120B Q8, Qwen3.5-122B, Scout-class long-context. Buy for these models specifically, not for headroom in the abstract.
M5 Max 36GB (~$3,899-3,999) — the honest entry. 27B-class at Q8; skip if 70B is on your list.
M5 Pro anything — only if local AI is a side interest.

Should M4 Max Owners Upgrade?

No. Our M4 Max 128GB guide stands: same models fit, same quants, and 546 GB/s vs 614 GB/s is a difference you measure, not one you feel in chat. The M5’s prefill gains are real but do not justify a $6,899 replacement of a one-year-old machine. The upgrade case exists only if you are also moving up a memory tier — 36/48GB M4 Max to 128GB M5 Max changes what you can run, which is a different purchase than a speed bump.

One shortage-era note: used M4 Max 128GB machines are holding value unusually well, so the trade-in math is less painful than usual — but that same fact means there is no bargain on the other side of the trade either.

Common Mistakes

Buying M5 Pro 48GB for 70B models. It fits them; it does not run them pleasantly. Bandwidth, not capacity, is the binding constraint.
Comparing MoE benchmarks against dense expectations. 88 tok/s on gpt-oss 120B does not mean 88 tok/s on Llama 70B. Dense 70B Q4 on this chip lands far lower.
Sizing to the full 128GB. macOS and your apps need 15-20GB. The 84.7GB Qwen3-Coder-Next fits with full context; a 100GB+ model does not leave room to work.
Waiting for prices to drop. Apple repriced upward twice during the 2026 memory shortage. The RAM shortage logic applies: soldered memory is priced at order time, and the direction has been up.