llmrun

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.

96 GB unified92.5 GB for models400 GB/s27 TFLOPS FP162023
Memory
32 GB64 GB96 GB
Same chip in
MacBook Pro 16"Mac StudioMacBook Pro 14"

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

#ModelSpeedllmrun ScoreQuant · Memory
1
Qwen3.8 27BAlibabaHow to run →
Q4_K_M · 17.9 GB
16.1 tok/sQ4_K_M · 17.9 GB
2
Qwen3.6 27BAlibaba
Q4_K_M · 17.9 GB
16.1 tok/sQ4_K_M · 17.9 GB
3
Gemma 4 26B A4B ITGoogle
Q4_K_M · 16.5 GB
63.2 tok/sQ4_K_M · 16.5 GB
4
GPT OSS 120BOpenAI
Q4_K_M · 70.8 GB
51.0 tok/sQ4_K_M · 70.8 GB
5
NVIDIA Nemotron 3.5 Lightning 30B A3B BF16NVIDIA
Q4_K_M · 19.3 GB
64.3 tok/sQ4_K_M · 19.3 GB
See all 355 models on the MacBook Pro 16" M2 Max →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 Max (96 GB)

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.

Speed in 96 GB#2400 GB/s
Prompt reading#227 TFLOPS
For models92.5 GBmacOS keeps 3.5 GB
ChipM2 Maxreleased 2023

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 GB
35B MoE22 GB70B51.3 GB123B74.7 GB
35B MoE22 GB70B51.3 GB123B74.7 GB
For models 92.5 GBmacOS keeps 3.5 GBModel size at Q4

Everything on the size ladder fits. Two 27B-class models together use 35.7 GB and leave 56.8 GB free.

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 Qwen3.6 35B A3B.

Same chip, 32 GB less memoryMacBook Pro 16" M2 Max (64 GB)Apple · 60.5 GB for models · M2 Max
same speed▼ 32 GBno price
Same familySame chip, 64 GB less memoryMacBook Pro 16" M2 Max (32 GB)Apple · 28.5 GB for models · M2 Max
same speed▼ 64 GBno price
Same familyReads prompts 10× faster, 120 GB for modelsDGX SparkNVIDIA · 120 GB for models · GB10
▲ 10× promptssame speed▲ 27.5 GBabout $3,999
18% faster, 32 GB more memoryMac Studio M4 Max (128 GB)Apple · 124.5 GB for models · M4 Max
▲ 18% speed▲ 32 GBabout $3,499
2.8× faster if your models fit in 24 GBRTX 4090NVIDIA · 24 GB VRAM · GPU
▲ 177% speed▼ 68.5 GBabout $1,599rent $0.34/hr
3.9× faster if your models fit in 32 GBRTX 5090NVIDIA · 32 GB VRAM · GPU
▲ 291% speed▼ 60.5 GBabout $5,376rent $0.64/hr

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

Output speed depends on memory bandwidth (400 GB/s). Grey rows need more than the 92.5 GB available.

  1. 9BQwen3.5 9B · Q4_K_M · 6.6 GB
    44.0tok/s
  2. 14BQwen3 14B · Q4_K_M · 11.9 GB
    29.5tok/s
  3. 27–31BQwen3.8 27B · Q4_K_M · 17.9 GB
    16.1tok/s
  4. 35B MoEQwen3.6 35B A3B · Q4_K_M · 22.0 GB
    54.5tok/s
  5. 70BLlama 3.3 70B Instruct · Q4_K_M · 51.3 GB slow
    6.0tok/s
  6. 120B MoEGPT OSS 120B · Q4_K_M · 70.8 GB
    51.0tok/s

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

Max generations: writing vs compute

M1 Max → M5 Max
Writing speed (tok/s)Compute (TFLOPS FP16)
1×2×3×4×M1 Max2021M2 Max2023M3 Max2023M4 Max2024M5 Max2026M1 Max · 20.8 TFLOPS FP16M1 Max · 54.5 tok/s · 400 GB/sM2 Max · 27.2 TFLOPS FP16M2 Max · 54.5 tok/s · 400 GB/sM3 Max · 21.5 TFLOPS FP16M3 Max · 45.9 tok/s · 300 GB/sM4 Max · 34.4 TFLOPS FP16M4 Max · 64.2 tok/s · 546 GB/sM5 Max · 68 TFLOPS FP16M5 Max · 67.8 tok/s · 614 GB/sCompute 3.3×Writing +24%
1×2×3×4×M12021M22023M32023M42024M52026M1 Max · 20.8 TFLOPS FP16M1 Max · 54.5 tok/s · 400 GB/sM2 Max · 27.2 TFLOPS FP16M2 Max · 54.5 tok/s · 400 GB/sM3 Max · 21.5 TFLOPS FP16M3 Max · 45.9 tok/s · 300 GB/sM4 Max · 34.4 TFLOPS FP16M4 Max · 64.2 tok/s · 546 GB/sM5 Max · 68 TFLOPS FP16M5 Max · 67.8 tok/s · 614 GB/sCompute 3.3×Writing +24%

Writing 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 only

Best quant that fits in 92.5 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 Max (96 GB) — ranked by Score, recency and Fit
ModelVRAMScoreFit
RedPajama INCITE 7B Base
7B·Q4_K_M·60.6 t/s·2K ctx
4.6 GBA84, Runs well
Xgen 7B 8k Base
7B·Q4_K_M·60.6 t/s·8K ctx
5.7 GBA84, Runs well
SmolLM 135M
135M·Q4_K_M·651.2 t/s·2K ctx
0.4 GBS100, Runs great
Gemma 2 2B
2.6B·Q4_K_M·161.8 t/s
3.6 GBS97, Runs great
Mistral Large Instruct 2407
122.6B·Q4_K_M·3.5 t/s
86.4 GBD20, Barely runs
Mistral Nemo Base 2407
12.2B·Q4_K_M·34.7 t/s·131K ctx
11.0 GBA73, Runs well
Deepseek Coder 1.3B Instruct
1.3B·Q4_K_M·185.4 t/s·16K ctx
4.3 GBS99, Runs great
Meta Llama 3 70B Instruct
70.6B·Q4_K_M·6.0 t/s
51.3 GBC43, Usable
MiMo v2 Flash
309.8B·IQ2_XXS·38.7 t/s·262K ctx
86.3 GBB55, Decent
Qwen2.5 Coder 3B
3.1B·Q4_K_M·125.6 t/s·33K ctx
2.8 GBS95, Runs great
Meta Llama 3 8B Instruct
8.0B·Q4_K_M·51.9 t/s·8K ctx
6.2 GBA81, Runs well
Meta Llama 3 70B
70.6B·Q4_K_M·6.0 t/s
51.3 GBC43, Usable
Qwen2 1.5B
1.5B·Q4_K_M·218.8 t/s·131K ctx
1.7 GBS100, Runs great
OpenReasoning Nemotron 32B
32.8B·Q4_K_M·13.7 t/s·131K ctx
24.3 GBB53, Decent
Llama 3.3 Nemotron 70B Reward
70.6B·Q4_K_M·6.5 t/s·131K ctx
48 GBC43, Usable

MacBook Pro 16" M2 Max specs

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 $1.00/hr.

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