Apple · M5 Pro · Laptop
Best AI Models for MacBook Pro 16" M5 Pro (24 GB)
Runs 14B models well and fits 35B MoE; dense 27–31B fits but is slow at 12 tok/s, and 70B doesn't fit in 20.5 GB.
| # | Model | Speed | Score |
|---|---|---|---|
| 1 | Qwen3.8 27BAlibabaHow to run → Q4_K_M · 17.9 GB | 12.3 tok/s | |
| 2 | Qwen3.6 27BAlibaba Q4_K_M · 17.9 GB | 12.3 tok/s | |
| 3 | Gemma 4 26B A4B ITGoogle Q4_K_M · 16.5 GB | 53.2 tok/s | |
| 4 | GPT OSS 20BOpenAI Q4_K_M · 13.1 GB | 59.3 tok/s | |
| 5 | MiniCPM5 2BOpenBMB Q4_K_M · 2.5 GB | 113 tok/s |
| # | Model | Speed | Score |
|---|---|---|---|
| 1 | Q4_K_M · 16.5 GB | 53.2 tok/s | |
| 2 | GPT OSS 20BOpenAI Q4_K_M · 13.1 GB | 59.3 tok/s | |
| 3 | Q4_K_M · 7.9 GB | 40.5 tok/s | |
| 4 | Qwen3.8 27BAlibaba Q4_K_M · 17.9 GB | 12.3 tok/s | |
| 5 | MiniCPM5 2BOpenBMB Q4_K_M · 2.5 GB | 113 tok/s |
| # | Model | Speed | Score |
|---|---|---|---|
| 1 | Q4_K_M · 16.5 GB | 53.2 tok/s | |
| 2 | Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB | 33.8 tok/s | |
| 3 | GPT OSS 20BOpenAI Q4_K_M · 13.1 GB | 59.3 tok/s | |
| 4 | Qwen3 8BAlibaba Q4_K_M · 7.6 GB | 38.9 tok/s | |
| 5 | MiniCPM5 2BOpenBMB Q4_K_M · 2.5 GB | 113 tok/s |
| # | Model | Speed | Score |
|---|---|---|---|
| 1 | Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB | 33.8 tok/s | |
| 2 | GPT OSS 20BOpenAI Q4_K_M · 13.1 GB | 59.3 tok/s | |
| 3 | Mistral Nemo Instruct 2407Mistral AI Q4_K_M · 11.0 GB | 26.6 tok/s | |
| 4 | Q4_K_M · 7.9 GB | 40.5 tok/s | |
| 5 | MiniCPM5 2BOpenBMB Q4_K_M · 2.5 GB | 113 tok/s |
| # | Model | Speed ↓ | Score |
|---|---|---|---|
| 1 | GPT OSS 20BOpenAIHow to run → Q4_K_M · 13.1 GB | 59.3 tok/s | |
| 2 | MiniCPM5 2BOpenBMB Q4_K_M · 2.5 GB | 113 tok/s | |
| 3 | Gemma 4 26B A4B ITGoogle Q4_K_M · 16.5 GB | 53.2 tok/s | |
| 4 | Qwen3 8BAlibaba Q4_K_M · 7.6 GB | 38.9 tok/s | |
| 5 | Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB | 33.8 tok/s |
| # | Model | Speed | Score |
|---|---|---|---|
| 1 | Q4_K_M · 16.5 GB | 53.2 tok/s | |
| 2 | Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB | 33.8 tok/s | |
| 3 | Gemma 3 12B ITGoogle Q4_K_M · 10.9 GB | 26.7 tok/s | |
| 4 | Qwen3.8 27BAlibaba Q4_K_M · 17.9 GB | 12.3 tok/s | |
| 5 | Q4_K_M · 6.5 GB | 34.6 tok/s |
The MacBook Pro 16" M5 Pro is the fastest 24 GB machine: it runs 14B models well and fits 35B MoE. macOS keeps about 3.5 GB, leaving 20.5 GB for models. With 32 TFLOPS it reads long prompts faster than most 24 GB machines: a 4K-token prompt takes 35 s. M5 Pro generation, released 2026.
MacBook Pro 16" M5 Pro strengths and weaknesses
Strengths
- Runs 35B MoE models: Qwen3.6 35B A3B at 49.7 tok/s in 19.8 GB
Weaknesses
- 70B models don't fit: Llama 3.3 70B Instruct needs 51.3 GB at Q4 vs 20.5 GB usable here
- Slow on large dense models: Qwen3.8 27B at 12.3 tok/s
- Slow prompt reading: A 32K-token prompt on Qwen3.8 27B waits 4.7 min for the first token
- No CUDA: vLLM, AWQ, GPTQ and FP8 builds don't run; use GGUF or MLX
Memory for models
20.5 GB of 24 GB70B models need 51.3 GB at Q4, more than the 20.5 GB available. The 48 GB config fits Qwen3.8 27B →
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 Qwen3.5 9B.
Output speed depends on memory bandwidth (307 GB/s). Grey rows need more than the 20.5 GB available.
- 9BQwen3.5 9B · Q4_K_M · 6.6 GB33.8tok/s
- 14BQwen3 14B · Q4_K_M · 11.9 GB22.6tok/s
- 27–31BQwen3.8 27B · Q4_K_M · 17.9 GB12.3tok/s
- 49.7tok/s
- 70BLlama 3.3 70B Instruct · does not fitneeds 51.3 GB
- 120B MoEGPT OSS 120B · does not fitneeds 70.8 GB
Estimated speeds: Q4_K_M, 4K context, one user. How we estimate
Pro generations: writing vs compute
M1 Pro → M5 ProWriting speed follows memory bandwidth and barely moved: 22.0 to 33.8 tok/s since the M1 Pro. Compute, which sets how fast prompts are read, grew 3.1×. Indexed to the M1 Pro; speeds on Qwen3.5 9B, same 16 GB.
All 1068 models on the MacBook Pro 16" M5 Pro
Featured onlyBest quant that fits in 20.5 GB, ordered by llmrun Score. Fit grades how well it runs here, S best. How ranking works
| Model | Quant | VRAM | Speed | Context | Score | Fit |
|---|---|---|---|---|---|---|
Steerling 8BChat | BF16 | 21.1 GB | — | — | F0, Won't fit | |
Gemma 7BChat | BF16 | 21.4 GB | — | — | F0, Won't fit | |
Gemma 7B ITChat | BF16 | 21.4 GB | — | — | F0, Won't fit |
Specs
- Chip
- M5 Pro
- CPU cores
- 18
- GPU cores
- 20
- Unified memory
- 24 GB
- For models
- 20.5 GB (macOS keeps 3.5 GB)
- Memory bandwidth
- 307 GB/s
- FP16 (dense)
- 32.3 TFLOPS
- Neural Engine
- 38 TOPS
- Released
- 2026-03-11
MacBook Pro 16" M5 Pro FAQ
How much memory is available for AI on the MacBook Pro 16" M5 Pro (24 GB)?
About 20.5 GB of the 24 GB. macOS keeps roughly 3.5 GB for itself and other apps.
What is the largest model the MacBook Pro 16" M5 Pro (24 GB) can run?
Qwen3.6 35B A3B (36.0B) at IQ4_XS uses 19.8 GB, 97% of the available memory, and runs at about 49.7 tok/s.
Can the MacBook Pro 16" M5 Pro (24 GB) run Qwen3.8 27B?
Yes. Qwen3.8 27B fits at Q4_K_M, using 17.9 GB of the 20.5 GB available, and it is the best model that runs well on this machine.
Can the MacBook Pro 16" M5 Pro (24 GB) run 70B models?
No. Llama 3.3 70B Instruct needs 51.3 GB at Q4, more than the 20.5 GB available.
How long does the MacBook Pro 16" M5 Pro (24 GB) take to read a long prompt?
On Qwen3.8 27B, about 35 s for a 4K-token prompt and 4.7 min for a 32K-token document before the first word appears.
Is renting a GPU cheaper than buying the MacBook Pro 16" M5 Pro?
An RTX 3090 (24 GB) rents from $0.18/hr.