Sunk Cost sunkcost.ai Data checked 2026-09-03

Can a MacBook Pro M5 Max (16-inch), 64GB run local LLMs?

Yes — 32 of the 48 current models on this site fit in its 48 GB of usable memory. The strongest it holds, Qwen3.8 27B, runs at 25 tok/s with a 32k window, worked out from memory bandwidth. Whether that saves you money is a different question: at $5,399 and 500k tokens a day, it pays back in 304 years.

Price$5,399
Memory64 GB, about 48 GB of it addressable by the GPU at 614 GB/s
Best model it runsQwen3.8 27B — Sonnet-class, 25 tok/s estimated
Pay-back against the APIPays back in 304 years at 500k tokens a day

Run the numbers on this machine

What the MacBook Pro M5 Max (16-inch), 64GB runs

They do not all hold the same window. The weights are a fixed size, but the key-value cache grows with every token you keep, so what is left of 48 GB after the weights is how far the context goes. On one of the 12 below, this machine's memory is what runs out first: Granite 4.2 30B stops soonest, at 64k. The rest reach 256k, where the calculator's list ends, or the longest setting their own context limit allows.

ModelSpeedClassMemoryLongest context
Qwen3.8 27BQ4_K_M 25 tok/s estimated Sonnet-class 19 GB 256k
Qwen3.6 27BQ4_K_M 24 tok/s estimated Haiku-class 19 GB 256k
Nemotron 3.5 Bolt 74B-A9BIQ2 63 tok/s estimated Haiku-class 22 GB 256k
Qwen3.6 35B-A3BQ4_K_M 73 tok/s estimated Haiku-class 23 GB 256k
Muse Glimmer 30BQ4_K_M 26 tok/s estimated Haiku-class 18 GB 128k
Gemma 4 26B-A4BQ4_K_M 54 tok/s estimated Haiku-class 18 GB 256k
Gemma 4 31B itQ4_K_M 20 tok/s estimated Haiku-class 23 GB 256k
Granite 4.2 30BQ4_K_M 18 tok/s estimated Haiku-class 26 GB 64kmemory
GLM-4.7-FlashQ4_K_M 52 tok/s estimated Haiku-class 20 GB 128k
Gemma 4 12BQ4_K_M 58 tok/s estimated Below every hosted tier 8.0 GB 256k
Qwen3.5 9BQ4_K_M 68 tok/s estimated Below every hosted tier 6.8 GB 256k
Nemotron 3.5 Lightning 30B-A3BQ4_K_M 70 tok/s estimated Below every hosted tier 26 GB 256k

Speed and memory are at 32k context, the setting the calculator starts on; the memory column is the weights plus the cache for that much of it. Each speed says how it was arrived at, and every one here is estimated from this machine's 614 GB/s of memory bandwidth rather than taken from a published benchmark. There is a page on how that sum works, and what each size needs, and one on what 64 GB runs, machine by machine. The longest context is the longest setting the calculator offers that this machine still holds the model at, cache included, and each one opens the calculator on that model at that length. A figure tagged memory is one this machine ran out of room for, and the rest are stopped by the model's own limit or by the end of the list.

For scale, the calculator starts from 80 tok/s for a hosted API and times a local machine against it. Nothing above reaches it, and the quickest is 73 tok/s.

On a laptop, sustained speed drops once the chassis warms up and the fans cap out, so a desktop with the same chip will hold a higher tokens/sec over a long generation than the figures here suggest.

20 more fit. Ranked below the twelve above: MiniCPM5 2B, Qwen3.5 4B, Ling 3.0 tiny, Granite 4.2 8B, Qwen3-Coder 30B-A3B, gpt-oss-20b, Gemma 4 E4B, LFM2.5 2.6B, Devstral Small 2 24B, Ministral 3 14B, Ministral 3 8B. The other 9 have no intelligence-index score, so the ranking cannot place them: Laguna XS 2.1, LFM3 1.7B, Ornith 1.5 9B, Ornith 1.5 35B-A3B, Spark-X2.5 4B, Spark-X2.6 4B, KAT-Coder V2.5 Dev 35B-A3B, LFM2.5 24B-A2B, Flint 40B-A2.5B. Their pages show what each one needs and what runs it.

The 48 counted above are the current models. This site prices 16 superseded ones as well, because people still run them, and this machine holds 11 of those at 32k, strongest first: Qwen3 30B-A3B Instruct 2507, DeepSeek-R1-Distill-Qwen-32B, Llama 3.1 8B Instruct at Q4_K_M, Llama 3.1 8B Instruct at Q8_0, Mistral Small 3.2 24B Instruct, Qwen3 32B at Q4_K_M, Qwen3 32B at Q8_0, Qwen3 14B, Qwen3 8B, Gemma 3 27B it, Gemma 3 12B it. Each of those pages asks whether the model is still worth running.

Other machines to weigh against the MacBook Pro M5 Max (16-inch), 64GB

MachinePriceMemoryModels that fitPay-back
The rest of the MacBook Pro range
MacBook Pro M5 (14-inch), 16GB $1,999 16 GB 12 Pays back in 157 years
MacBook Pro M5 (14-inch), 32GB $2,399 32 GB 22 Pays back in 157 years
MacBook Pro M5 Pro (16-inch), 24GB $2,999 24 GB 16 Pays back in 239 years
MacBook Pro M5 Pro (16-inch), 48GB $3,599 48 GB 32 Pays back in 242 years
MacBook Pro M5 Pro (16-inch), 64GB $3,999 64 GB 32 Pays back in 269 years
MacBook Pro M5 Max (16-inch), 48GB $4,999 48 GB 32 Pays back in 281 years
MacBook Pro M5 Max (16-inch), 128GB $6,999 128 GB 39 Pays back in 393 years
Nearest in price elsewhere on the list
NVIDIA GeForce RTX 5090, 32GB $1,999card only 32 GB 32 Pays back in 123 years
Mac mini M5 Pro, 64GB $2,699 64 GB 32 Pays back in 182 years
DGX Spark GB10 Grace Blackwell, 128GB $4,699 128 GB 39 Pays back in 346 years
Mac Studio M5 Ultra, 96GB $5,499 96 GB 34 Pays back in 307 years
Strix Halo HP Z2 Mini G1a, 128GB $5,544 128 GB 39 Pays back in 396 years

Every row uses the same defaults as the figures above: 500k tokens a day at 15:1 input to output, 32k context, and each machine's strongest model that fits, counted against the same 48 current models. The GeForce RTX 5090, 32GB is priced as the card alone, so add the PC around it before comparing it with a complete computer. All seven cards here are ranked by what each one holds.

Head to head with another computer: Mac Studio M5 Ultra, 96GB. With the same machine at another memory size: 48GB · 128GB. There are 111 machine match-ups on the site.

The specifics

Chip
M5 Max (16-inch) — 18-core CPU / 40-core GPU
Memory bandwidth
614 GB/s
Usable by the GPU
48 GB — macOS lets the GPU wire roughly 75% of unified memory by default (llama.cpp discussion #2182: 66.7% at 32 GiB or less, 75% above). Raise it with `sudo sysctl iogpu.wired_limit_mb`.
Power under load
145 W (stand-in) — Apple has published no power figures for the 2026 Macs, and none at all for sustained GPU load on a laptop. Stand-in: the desktop maximum for the equivalent chip (M4 Max Mac Studio, 145 W). A laptop draws less than that, so the electricity line here is an over-estimate.
Availability
Shipping.
Sources
Apple (specs), Apple (store), Apple Support