Apple · M2 Max · Laptop
Best AI Models for MacBook Pro 16" M2 Max (96 GB)
Runs 27–31B and 120B MoE models well; dense 70B fits but is slow at 6 tok/s.
| # | Model | Speed | Score |
|---|---|---|---|
| 1 | Qwen3.8 27BAlibabaHow to run → Q4_K_M · 17.9 GB | 16.1 tok/s | |
| 2 | Qwen3.6 27BAlibaba Q4_K_M · 17.9 GB | 16.1 tok/s | |
| 3 | Gemma 4 26B A4B ITGoogle Q4_K_M · 16.5 GB | 63.2 tok/s | |
| 4 | GPT OSS 120BOpenAI Q4_K_M · 70.8 GB | 51.0 tok/s | |
| 5 | Q4_K_M · 19.3 GB | 64.3 tok/s |
| # | Model | Speed | Score |
|---|---|---|---|
| 1 | Qwen3.8 27BAlibabaHow to run → Q4_K_M · 17.9 GB | 16.1 tok/s | |
| 2 | Qwen3.6 35B A3BAlibaba Q4_K_M · 22.0 GB | 54.5 tok/s | |
| 3 | Gemma 4 26B A4B ITGoogle Q4_K_M · 16.5 GB | 63.2 tok/s | |
| 4 | GPT OSS 20BOpenAI Q4_K_M · 13.1 GB | 71.2 tok/s | |
| 5 | Q4_K_M · 19.3 GB | 64.3 tok/s |
| # | Model | Speed | Score |
|---|---|---|---|
| 1 | Qwen3.8 27BAlibabaHow to run → Q4_K_M · 17.9 GB | 16.1 tok/s | |
| 2 | Qwen3.5 27BAlibaba Q4_K_M · 17.9 GB | 16.1 tok/s | |
| 3 | Gemma 4 26B A4B ITGoogle Q4_K_M · 16.5 GB | 63.2 tok/s | |
| 4 | GPT OSS 120BOpenAI Q4_K_M · 70.8 GB | 51.0 tok/s | |
| 5 | Q4_K_M · 19.3 GB | 64.3 tok/s |
| # | Model | Speed | Score |
|---|---|---|---|
| 1 | Qwen3.8 27BAlibabaHow to run → Q4_K_M · 17.9 GB | 16.1 tok/s | |
| 2 | Qwen3.6 27BAlibaba Q4_K_M · 17.9 GB | 16.1 tok/s | |
| 3 | Qwen3.6 35B A3BAlibaba Q4_K_M · 22.0 GB | 54.5 tok/s | |
| 4 | Gemma 4 26B A4B ITGoogle Q4_K_M · 16.5 GB | 63.2 tok/s | overall |
| 5 | Q4_K_M · 19.3 GB | 64.3 tok/s |
| # | Model | Speed ↓ | Score |
|---|---|---|---|
| 1 | GPT OSS 20BOpenAIHow to run → Q4_K_M · 13.1 GB | 71.2 tok/s | |
| 2 | Q4_K_M · 19.3 GB | 64.3 tok/s | |
| 3 | Gemma 4 26B A4B ITGoogle Q4_K_M · 16.5 GB | 63.2 tok/s | |
| 4 | Qwen3 30B A3B Thinking 2507Alibaba Q4_K_M · 19.4 GB | 59.0 tok/s | |
| 5 | Qwen3 30B A3B Instruct 2507Alibaba Q4_K_M · 19.4 GB | 59.0 tok/s |
The MacBook Pro 16" M2 Max is one of the fastest 96 GB machines: it runs 27–31B and 120B MoE models well. Among 96 GB machines, only the M3 Ultra write faster. macOS keeps about 3.5 GB, leaving 92.5 GB for models. With 27 TFLOPS it reads long prompts faster than most 96 GB machines: a 4K-token prompt takes 42 s. M2 Max generation, released 2023; the newer M3 Max writes -16% faster with 0.8× the compute.
MacBook Pro 16" M2 Max strengths and weaknesses
Strengths
- Runs 120B MoE models: GPT OSS 120B at 51.0 tok/s in 70.8 GB
- Room for long context: Qwen3.8 27B at Q4 uses 17.9 GB, leaving 74.6 GB free
Weaknesses
- Slow on large dense models: Llama 3.3 70B Instruct at 6.0 tok/s
- Slow prompt reading: A 32K-token prompt on Qwen3.8 27B waits 5.6 min for the first token
- No CUDA: vLLM, AWQ, GPTQ and FP8 builds don't run; use GGUF or MLX
Memory for models
92.5 GB of 96 GBEverything on the size ladder fits. Two 27B-class models together use 35.7 GB and leave 56.8 GB free.
Other memory sizes of the same machine first, then machines and GPUs people weigh against it, each with the one reason it is worth a look. Speeds on Qwen3.6 35B A3B.
Output speed depends on memory bandwidth (400 GB/s). Grey rows need more than the 92.5 GB available.
- 9BQwen3.5 9B · Q4_K_M · 6.6 GB44.0tok/s
- 14BQwen3 14B · Q4_K_M · 11.9 GB29.5tok/s
- 27–31BQwen3.8 27B · Q4_K_M · 17.9 GB16.1tok/s
- 35B MoEQwen3.6 35B A3B · Q4_K_M · 22.0 GB54.5tok/s
- 6.0tok/s
- 120B MoEGPT OSS 120B · Q4_K_M · 70.8 GB51.0tok/s
Estimated speeds: Q4_K_M, 4K context, one user. How we estimate
Max generations: writing vs compute
M1 Max → M5 MaxWriting speed follows memory bandwidth and barely moved: 54.5 to 67.8 tok/s since the M1 Max. Compute, which sets how fast prompts are read, grew 3.3×. Indexed to the M1 Max; speeds on Qwen3.6 35B A3B, same 64 GB.
All 1206 models on the MacBook Pro 16" M2 Max
Featured onlyBest quant that fits in 92.5 GB, ordered by llmrun Score. Fit grades how well it runs here, S best. How ranking works
| Model | Quant | VRAM | Speed | Context | Score | Fit |
|---|---|---|---|---|---|---|
CodeLlama 7B HFChatCode | Q4_K_M | 12.9 GB | 51.7 t/s | 16K | A80, Runs well | |
Phi 3 Mini 128k InstructChatCode | Q4_K_M | 9.0 GB | 82.4 t/s | 131K | S88, Runs great | |
Shieldgemma 2BChat | Q4_K_M | 3.6 GB | 161.8 t/s | — | S97, Runs great | |
Qwen 1 8BChat | Q4_K_M | 1.9 GB | 231.4 t/s | 8K | S100, Runs great | |
| Q4_K_M | 4.6 GB | 155.6 t/s | 33K | S97, Runs great | ||
| Q4_K_M | 6.8 GB | 57.0 t/s | 33K | A82, Runs well | ||
Gemma 1.1 2B ITChat | Q4_K_M | 3.5 GB | 169.7 t/s | — | S98, Runs great | |
| Q4_K_M | 49.3 GB | 6.3 t/s | 33K | C43, Usable | ||
Phi 3 Medium 128k InstructChatCode | Q4_K_M | 12.0 GB | 30.8 t/s | 131K | A71, Runs well | |
Codegemma 2BChatCode | Q4_K_M | 3.5 GB | 169.7 t/s | — | S98, Runs great | |
Qwen2 VL 72B InstructVision | Q4_K_M | 49.7 GB | 6.2 t/s | 33K | C43, Usable | |
Qwen2.5 3BChatFunctions | Q4_K_M | 2.8 GB | 125.6 t/s | 33K | S95, Runs great | |
Yi 6B ChatChat | Q4_K_M | 4.2 GB | 68.8 t/s | 4K | S85, Runs great | |
StarcoderChatCode | Q4_K_M | 13.6 GB | 26.8 t/s | — | A68, Runs well | |
| Q4_K_M | 5.0 GB | 60.6 t/s | 4K | A84, Runs well |
Specs
- Chip
- M2 Max
- CPU cores
- 12
- GPU cores
- 38
- Unified memory
- 96 GB
- For models
- 92.5 GB (macOS keeps 3.5 GB)
- Memory bandwidth
- 400 GB/s
- FP16 (dense)
- 27.2 TFLOPS
- Neural Engine
- 16 TOPS
- Released
- 2023-01-24
MacBook Pro 16" M2 Max FAQ
How much memory is available for AI on the MacBook Pro 16" M2 Max (96 GB)?
About 92.5 GB of the 96 GB. macOS keeps roughly 3.5 GB for itself and other apps.
What is the largest model the MacBook Pro 16" M2 Max (96 GB) can run?
NVIDIA Nemotron 3 Super 120B A12B BF16 (123.6B) at Q4_K_M uses 74.7 GB, 81% of the available memory, and runs at about 21.9 tok/s.
Can the MacBook Pro 16" M2 Max (96 GB) run Qwen3.8 27B?
Yes. Qwen3.8 27B fits at Q4_K_M, using 17.9 GB of the 92.5 GB available, and it is the best model that runs well on this machine.
Can the MacBook Pro 16" M2 Max (96 GB) run 70B models?
Yes, but slowly: Llama 3.3 70B Instruct at Q4_K_M uses 51.3 GB and writes about 6.0 tok/s.
How long does the MacBook Pro 16" M2 Max (96 GB) take to read a long prompt?
On Qwen3.8 27B, about 42 s for a 4K-token prompt and 5.6 min for a 32K-token document before the first word appears.
Is renting a GPU cheaper than buying the MacBook Pro 16" M2 Max?
An RTX PRO 6000 Blackwell Max-Q Workstation Edition (96 GB) rents from $1.27/hr.