llmrun

Apple · M2 Max · Desktop

Best AI Models for Mac Studio M2 Max (64 GB)

Runs 27–35B models well and fits 120B MoE; dense 70B fits but is slow at 6 tok/s.

64 GB unified60.5 GB for models400 GB/s21 TFLOPS FP162023
Memory
32 GB64 GB96 GB
Same chip in
Mac StudioMacBook Pro 14"MacBook Pro 16"

What LLMs can the Mac Studio 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 20BOpenAI
Q4_K_M · 13.1 GB
71.2 tok/sQ4_K_M · 13.1 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 338 models on the Mac Studio 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 Mac Studio M2 Max (64 GB)

The Mac Studio M2 Max is a 64 GB desktop 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 53 s before the first word on Qwen3.8 27B. M2 Max generation, released 2023; the newer M3 Max writes 1% faster with 1.3× the compute.

Speed in 64 GB#6400 GB/s
Prompt reading#821 TFLOPS
For models60.5 GBmacOS keeps 3.5 GB
ChipM2 Maxreleased 2023

Mac Studio 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 7.1 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 GB
9B6.6 GB14B11.9 GB35B MoE22 GB70B51.3 GB120B MoE59.1 GB
35B MoE22 GB120B MoE59.1 GB
For models 60.5 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 24.8 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 memoryMac Studio M2 Max (32 GB)Apple · 28.5 GB for models · M2 Max
same speed▼ 32 GBno price
Same familySame chip, 32 GB more memoryMac Studio M2 Max (96 GB)Apple · 92.5 GB for models · M2 Max
same speed▲ 32 GBno price
Same family18% faster, same memoryMac Studio M4 Max (64 GB)Apple · 60.5 GB for models · M4 Max
▲ 18% speedsame memoryabout $2,699
41% faster, 11.5 GB more memoryMac Studio M3 Ultra (96 GB)Apple · 72 GB for models · M3 Ultra
▲ 41% speed▲ 11.5 GBabout $3,999
2.8× faster if your models fit in 24 GBRTX 4090NVIDIA · 24 GB VRAM · GPU
▲ 177% speed▼ 36.5 GBabout $1,599rent $0.34/hr
3.9× faster if your models fit in 32 GBRTX 5090NVIDIA · 32 GB VRAM · GPU
▲ 291% speed▼ 28.5 GBabout $5,376rent $0.64/hr

Mac Studio M2 Max tokens per second by model size

Output speed depends on memory bandwidth (400 GB/s). Grey rows need more than the 60.5 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_0 · 59.1 GB tight · Q4_0
    57.0tok/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)
1×2×3×4×5×M1 Max2022M2 Max2023M3 Max2023M4 Max2025M5 Max2026M1 Max · 15.6 TFLOPS FP16M1 Max · 54.5 tok/s · 400 GB/sM2 Max · 21.5 TFLOPS FP16M2 Max · 54.5 tok/s · 400 GB/sM3 Max · 28.7 TFLOPS FP16M3 Max · 55.2 tok/s · 409.6 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 4.4×Writing +24%
1×2×3×4×5×M12022M22023M32023M42025M52026M1 Max · 15.6 TFLOPS FP16M1 Max · 54.5 tok/s · 400 GB/sM2 Max · 21.5 TFLOPS FP16M2 Max · 54.5 tok/s · 400 GB/sM3 Max · 28.7 TFLOPS FP16M3 Max · 55.2 tok/s · 409.6 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 4.4×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 4.4×. Indexed to the M1 Max; speeds on Qwen3.6 35B A3B, same 64 GB.

All 1168 models on the Mac Studio M2 Max

Featured only

Best quant that fits in 60.5 GB, ordered by llmrun Score. Fit grades how well it runs here, S best. How ranking works

LLM models compatible with Mac Studio M2 Max (64 GB) — ranked by Score, recency and Fit
ModelVRAMScoreFit
C4ai Command R V01
35.0B·Q4_K_M·12.1 t/s
27.0 GBB51, Decent
Qwen2 7B Instruct
7.6B·Q4_K_M·56.1 t/s·33K ctx
5.8 GBA82, Runs well
SmolLM 360M
362M·Q4_K_M·466.7 t/s·2K ctx
0.6 GBS100, Runs great
Chatglm2 6B
6B·Q4_K_M·70.7 t/s·33K ctx
6.3 GBS86, Runs great
Qwen3 4B Abliterated
4.0B·Q4_K_M·105.7 t/s
4.8 GBS92, Runs great
Llama 3.2 1B
1.2B·Q4_K_M·341.5 t/s
2.3 GBS100, Runs great
Qwen2.5 1.5B
1.5B·Q4_K_M·218.8 t/s·131K ctx
1.7 GBS100, Runs great
Yi 6B
6.1B·Q4_K_M·68.8 t/s·4K ctx
4.2 GBS85, Runs great
Qwen3 30B A3B Base
30.5B·Q4_K_M·59.0 t/s·33K ctx
19.4 GBA83, Runs well
Deepseek Coder 7B Instruct V1.5
6.9B·Q4_K_M·51.4 t/s·4K ctx
6.5 GBA80, Runs well
Qwen2.5 Math 7B Instruct
7.6B·Q4_K_M·56.1 t/s·4K ctx
5.1 GBA82, Runs well
SmolLM 360M Instruct
362M·Q4_K_M·466.7 t/s·2K ctx
0.6 GBS100, Runs great
Mistral Small Instruct 2409
22.2B·Q4_K_M·19.8 t/s·33K ctx
17.4 GBB60, Decent
Starcoder2 15B
16.0B·Q4_K_M·27.9 t/s·16K ctx
11.2 GBA69, Runs well
Falcon 7B
7.2B·Q4_K_M·58.8 t/s
7.3 GBA83, Runs well

Mac Studio M2 Max specs

Specs

Chip
M2 Max
CPU cores
12
GPU cores
30
Unified memory
64 GB
For models
60.5 GB (macOS keeps 3.5 GB)
Memory bandwidth
400 GB/s
FP16 (dense)
21.5 TFLOPS
Neural Engine
16 TOPS
Released
2023-06-13

Mac Studio M2 Max FAQ

How much memory is available for AI on the Mac Studio 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 Mac Studio 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 Mac Studio M2 Max (64 GB) run Qwen3.8 27B?

Yes. Qwen3.8 27B fits at Q4_K_M, using 17.9 GB of the 60.5 GB available, and it is the best model that runs well on this machine.

Can the Mac Studio 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 Mac Studio M2 Max (64 GB) take to read a long prompt?

On Qwen3.8 27B, about 53 s for a 4K-token prompt and 7.1 min for a 32K-token document before the first word appears.

Is renting a GPU cheaper than buying the Mac Studio M2 Max?

An A100 (80 GB) rents from $1.07/hr.

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