Apple · M2 Max · Laptop
Best AI Models for MacBook Pro 14" M2 Max (64 GB)
Runs 27–35B models well and fits 120B MoE; 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 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 | Qwen3.6 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 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 | Qwen3.6 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 14" M2 Max is a 64 GB laptop with more memory than speed: it runs 27–35B models well and fits 120B MoE. macOS keeps about 3.5 GB, leaving 60.5 GB for models. Prompt reading is its weak spot: a 4K-token prompt waits 42 s before the first word on Qwen3.8 27B. M2 Max generation, released 2023; the newer M3 Max writes 1% faster with 1.1× the compute.
MacBook Pro 14" M2 Max strengths and weaknesses
Strengths
- Runs 120B MoE models: GPT OSS 120B at 57.0 tok/s in 59.1 GB
- Room for long context: Qwen3.8 27B at Q4 uses 17.9 GB, leaving 42.6 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
60.5 GB of 64 GBEverything on the size ladder fits. Two 27B-class models together use 35.7 GB and leave 24.8 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 60.5 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
- 57.0tok/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 1168 models on the MacBook Pro 14" M2 Max
Featured onlyBest quant that fits in 60.5 GB, ordered by llmrun Score. Fit grades how well it runs here, S best. How ranking works
| Model | Quant | VRAM | Speed | Context | Score | Fit |
|---|---|---|---|---|---|---|
Dream V0 Instruct 7BChatFunctions | Q4_K_M | 5.8 GB | 56.1 t/s | 131K | A82, Runs well | |
MediPhi InstructChat | Q4_K_M | 9.0 GB | 82.4 t/s | 131K | S88, Runs great | |
Llama XLAM 2 8B Fc RChatFunctions | Q4_K_M | 7.3 GB | 51.9 t/s | 131K | A81, Runs well | |
| BF16 | 2.5 GB | 215.4 t/s | — | S100, Runs great | ||
| Q4_K_M | 27.0 GB | 12.1 t/s | — | B51, Decent | ||
Gemma 2 2B ITChat | Q4_K_M | 2.6 GB | 132.7 t/s | 8K | S95, Runs great | |
GLM 4.6V FlashVisionFunctions | Q4_K_M | 7.2 GB | 42.7 t/s | 131K | A76, Runs well | |
| Q4_K_M | 2.3 GB | 167.7 t/s | 4K | S98, Runs great | ||
| Q4_K_M | 7.3 GB | 51.9 t/s | 131K | A81, Runs well | ||
| Q4_K_M | 7.6 GB | 50.7 t/s | 41K | A80, Runs well | ||
| Q4_K_M | 4.2 GB | 96.6 t/s | 41K | S90, Runs great | ||
Idefics3 8B Llama3Vision | Q4_K_M | 7.5 GB | 49.6 t/s | 131K | A79, Runs well | |
MedScholar 1.5BChat | Q4_K_M | 1.7 GB | 218.8 t/s | 33K | S100, Runs great | |
| Q4_K_M | 30.5 GB | 28.9 t/s | 33K | A69, Runs well | ||
Qwen2.5 Omni 3BChat | Q4_K_M | 6.0 GB | 76.7 t/s | — | S87, Runs great |
Specs
- Chip
- M2 Max
- CPU cores
- 12
- GPU cores
- 38
- Unified memory
- 64 GB
- For models
- 60.5 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 14" M2 Max FAQ
How much memory is available for AI on the MacBook Pro 14" M2 Max (64 GB)?
About 60.5 GB of the 64 GB. macOS keeps roughly 3.5 GB for itself and other apps.
What is the largest model the MacBook Pro 14" M2 Max (64 GB) can run?
GPT OSS 120B (116.8B) at Q4_0 uses 59.1 GB, 98% of the available memory, and runs at about 57.0 tok/s.
Can the MacBook Pro 14" M2 Max (64 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 14" M2 Max (64 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 14" M2 Max?
An A100 (80 GB) rents from $1.07/hr.