llmrun

Apple · M2 Pro · Laptop

Best AI Models for MacBook Pro 16" M2 Pro (16 GB)

Runs 9B models well; 14B only just fits in 12.5 GB, and 27–31B doesn't fit.

16 GB unified12.5 GB for models200 GB/s14 TFLOPS FP162023
Memory
16 GB32 GB
Same chip in
MacBook Pro 16"Mac MiniMacBook Pro 14"

What LLMs can the MacBook Pro 16" M2 Pro run?

#ModelSpeedCoding ScoreQuant · Memory
1
Llama 3.1 8B InstructMetaHow to run →
Q4_K_M · 7.9 GB
26.4 tok/sQ4_K_M · 7.9 GB
2
Qwen3.5 9BAlibaba
Q4_K_M · 6.6 GB
22.0 tok/soverall Q4_K_M · 6.6 GB
3
Qwen3 8BAlibaba
Q4_K_M · 7.6 GB
25.4 tok/soverall Q4_K_M · 7.6 GB
4
Gemma 4 12B ITGoogle
Q4_K_M · 9.0 GB
17.0 tok/sQ4_K_M · 9.0 GB
5
Gemma 4 E4B ITGoogle
Q4_K_M · 5.6 GB
26.3 tok/sQ4_K_M · 5.6 GB
See all 257 models on the MacBook Pro 16" M2 Pro →Bars = traction for models without a Score yet
Task rankings use that task's benchmarks, topped up from Overall when short; bars mark well-known models with no Score yet.

About the MacBook Pro 16" M2 Pro (16 GB)

The MacBook Pro 16" M2 Pro is the fastest 16 GB machine: it runs 9B models well. macOS keeps about 3.5 GB, leaving 12.5 GB for models. Prompt reading is its weak spot: a 4K-token prompt waits 29 s before the first word on Qwen3.5 9B. M2 Pro generation, released 2023; the newer M3 Pro writes -25% faster with 1.0× the compute.

Speed in 16 GB#1200 GB/s
Prompt reading#314 TFLOPS
For models12.5 GBmacOS keeps 3.5 GB
ChipM2 Proreleased 2023

MacBook Pro 16" M2 Pro strengths and weaknesses

Strengths

  • Runs 7–9B models: Qwen3.5 9B at 22.0 tok/s in 6.6 GB

Weaknesses

  • 27–31B models don't fit: Qwen3.8 27B needs 17.9 GB at Q4 vs 12.5 GB usable here
  • Little room for context: Qwen3 14B uses 11.9 of 12.5 GB usable, 0.6 GB left
  • Slow prompt reading: A 32K-token prompt on Qwen3.5 9B waits 3.9 min for the first token
  • No CUDA: vLLM, AWQ, GPTQ and FP8 builds don't run; use GGUF or MLX

Memory for models

12.5 GB of 16 GB
9B6.6 GB14B11.9 GB
9B6.6 GB14B11.9 GB
For models 12.5 GBmacOS keeps 3.5 GBModel size at Q4

27–31B models need 17.9 GB at Q4, more than the 12.5 GB available. The 32 GB config fits Qwen3.8 27B →

Similar devices and alternatives

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.

Same chip, 2× the memoryMacBook Pro 16" M2 Pro (32 GB)Apple · 28.5 GB for models · M2 Pro
same speed▲ 16 GBno price
Same familyNewer machine, 40% slowerMac Mini M4 (16 GB)Apple · 12.5 GB for models · M4
▼ 40% speedsame memoryabout $799
36% faster, 8 GB more memoryMac Mini M4 Pro (24 GB)Apple · 20.5 GB for models · M4 Pro
▲ 36% speed▲ 8 GBabout $1,599
105% faster, 20 GB more memoryMac Studio M4 Max (36 GB)Apple · 32.5 GB for models · M4 Max
▲ 105% speed▲ 20 GBabout $2,499
Reads prompts 27× faster, 24 GB for modelsRTX 4090NVIDIA · 24 GB VRAM · GPU
▲ 27× prompts▲ 368% speed▲ 11.5 GBabout $1,599rent $0.34/hr
Reads prompts 35× faster, 32 GB for modelsRTX 5090NVIDIA · 32 GB VRAM · GPU
▲ 35× prompts▲ 732% speed▲ 19.5 GBabout $5,376rent $0.64/hr

MacBook Pro 16" M2 Pro tokens per second by model size

Output speed depends on memory bandwidth (200 GB/s). Grey rows need more than the 12.5 GB available.

  1. 9BQwen3.5 9B · Q4_K_M · 6.6 GB
    22.0tok/s
  2. 14BQwen3 14B · Q4_K_M · 11.9 GB tight · Q4_K_M
    14.7tok/s
  3. 27–31BQwen3.8 27B · does not fit
    needs 17.9 GB
  4. 35B MoEQwen3.6 35B A3B · does not fit
    needs 22.0 GB
  5. 70BLlama 3.3 70B Instruct · does not fit
    needs 51.3 GB
  6. 120B MoEGPT OSS 120B · does not fit
    needs 70.8 GB

Estimated speeds: Q4_K_M, 4K context, one user. How we estimate

Pro generations: writing vs compute

M1 Pro → M5 Pro
Writing speed (tok/s)Compute (TFLOPS FP16)
1×2×3×4×M1 Pro2021M2 Pro2023M3 Pro2023M4 Pro2024M5 Pro2026M1 Pro · 10.4 TFLOPS FP16M1 Pro · 22.0 tok/s · 200 GB/sM2 Pro · 13.6 TFLOPS FP16M2 Pro · 22.0 tok/s · 200 GB/sM3 Pro · 12.9 TFLOPS FP16M3 Pro · 16.5 tok/s · 150 GB/sM4 Pro · 17.2 TFLOPS FP16M4 Pro · 30.0 tok/s · 273 GB/sM5 Pro · 32.3 TFLOPS FP16M5 Pro · 33.8 tok/s · 307 GB/sCompute 3.1×Writing +54%
1×2×3×4×M12021M22023M32023M42024M52026M1 Pro · 10.4 TFLOPS FP16M1 Pro · 22.0 tok/s · 200 GB/sM2 Pro · 13.6 TFLOPS FP16M2 Pro · 22.0 tok/s · 200 GB/sM3 Pro · 12.9 TFLOPS FP16M3 Pro · 16.5 tok/s · 150 GB/sM4 Pro · 17.2 TFLOPS FP16M4 Pro · 30.0 tok/s · 273 GB/sM5 Pro · 32.3 TFLOPS FP16M5 Pro · 33.8 tok/s · 307 GB/sCompute 3.1×Writing +54%

Writing 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 257 models on the MacBook Pro 16" M2 Pro

Featured only

Best quant that fits in 12.5 GB, ordered by llmrun Score. Fit grades how well it runs here, S best. How ranking works

LLM models compatible with MacBook Pro 16" M2 Pro (16 GB) — ranked by Score, recency and Fit
ModelVRAMScoreFit
Qwen3.5 9B
9.7B·Q4_K_M·22.0 t/s·262K ctx
6.6 GBB62, Decent
Qwen3.5 4B
4.7B·Q4_K_M·42.9 t/s·262K ctx
3.4 GBA77, Runs well
Qwen3.8 27B
27.8B·IQ3_XXS·12.2 t/s·262K ctx
12.0 GBD26, Barely runs
Gemma 4 12B IT
12.0B·Q4_K_M·17.0 t/s·262K ctx
9.0 GBB56, Decent
Gemma 4 E4B IT
8.0B·Q4_K_M·26.3 t/s·131K ctx
5.6 GBA67, Runs well
Ling 3.0 Tiny
7.9B·Q4_K_M·87.1 t/s·131K ctx
5.5 GBS89, Runs great
MiniCPM5 2B
2.5B·Q4_K_M·73.7 t/s·131K ctx
2.5 GBS86, Runs great
LFM2.5 8B A1B
8.5B·Q4_K_M·79.4 t/s·128K ctx
5.6 GBS87, Runs great
Ornith 1.0 9B
9.4B·Q4_K_M·22.5 t/s·262K ctx
6.5 GBB63, Decent
MiMo V2.6 Distill Qwen 9B
9.4B·Q4_K_M·22.5 t/s·262K ctx
6.5 GBB63, Decent
Apertus V1.5 8B
8.9B·Q4_K_M·23.8 t/s
8.5 GBB64, Decent
Gemma 4 26B A4B IT
25.8B·Q3_K_S·48.7 t/s·262K ctx
12.3 GBC44, Usable
MinerU2.5 Pro 2605 1.2B
1.2B·Q4_K_M·137.3 t/s·8K ctx
1.1 GBS96, Runs great
MiniCPM O 4 5
9.4B·Q4_K_M·22.5 t/s·41K ctx
8.3 GBB63, Decent
ZAYA1 VL 8B
9.7B·Q4_K_M·89.0 t/s·33K ctx
7.5 GBS89, Runs great

MacBook Pro 16" M2 Pro specs

Specs

Chip
M2 Pro
CPU cores
12
GPU cores
19
Unified memory
16 GB
For models
12.5 GB (macOS keeps 3.5 GB)
Memory bandwidth
200 GB/s
FP16 (dense)
13.6 TFLOPS
Neural Engine
16 TOPS
Released
2023-01-24

MacBook Pro 16" M2 Pro FAQ

How much memory is available for AI on the MacBook Pro 16" M2 Pro (16 GB)?

About 12.5 GB of the 16 GB. macOS keeps roughly 3.5 GB for itself and other apps.

What is the largest model the MacBook Pro 16" M2 Pro (16 GB) can run?

GPT OSS 20B (20.9B) at Q4_K_S uses 12.4 GB, 99% of the available memory, and runs at about 45.1 tok/s.

Can the MacBook Pro 16" M2 Pro (16 GB) run Qwen3.5 9B?

Yes. Qwen3.5 9B fits at Q4_K_M, using 6.6 GB of the 12.5 GB available, and it is the best model that runs well on this machine.

Can the MacBook Pro 16" M2 Pro (16 GB) run 27–31B models?

No. Qwen3.8 27B needs 17.9 GB at Q4, more than the 12.5 GB available.

How long does the MacBook Pro 16" M2 Pro (16 GB) take to read a long prompt?

On Qwen3.5 9B, about 29 s for a 4K-token prompt and 3.9 min for a 32K-token document before the first word appears.

Is renting a GPU cheaper than buying the MacBook Pro 16" M2 Pro?

A Tesla V100 (16 GB) rents from $0.10/hr.

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