The best local LLM for a Mac Studio M2 Max (64 GB) is Qwen3.8-27B at 20 tok/s (estimated). With 64 GB of unified memory it runs 53 of the models in the LLMCheck index — from compact options up to 119B-class models. For everyday chat and coding, Qwen3.8-27B is the sweet spot. Full ranking below.
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Ranked by LLMCheck suitability (capability balanced against speed on the M2 Max). Click a model for its full benchmark and setup. Every speed carries its provenance mark: most are index estimates from the memory-bandwidth model, and a filled square is a published measurement — submit a real run →
| # | Model | Size | License | Speed | Capability |
|---|---|---|---|---|---|
| 1 | Qwen3.8-27B | 27.8B | Apache 2.0 | estimated20 tok/s | 46/50 |
| 2 | Qwen 3.6-27B | 27B | Apache 2.0 | estimated20 tok/s | 44/50 |
| 3 | Muse Glimmer 30B | 30B | Apache 2.0 | estimated15 tok/s | 42/50 |
| 4 | KAT-Coder-V2.5 | 35B | Apache 2.0 | estimated35 tok/s | 39/50 |
| 5 | Gemma 4 31B | 31B | Apache 2.0 | estimated17 tok/s | 40/50 |
| 6 | Qwen 3.6-35B-A3B | 35B | Apache 2.0 | estimated32 tok/s | 38/50 |
| 7 | Gemma 4 26B-A4B | 26B | Apache 2.0 | estimated50 tok/s | 35/50 |
| 8 | Nemotron 3.5 Lightning | 30B | OpenMDW | estimated40 tok/s | 36/50 |
| 9 | Qwen3-Coder-Next | 80B | Apache 2.0 | estimated24 tok/s | 35/50 |
| 10 | Laguna XS 2.1 | 33B | OpenMDW | estimated36 tok/s | 33/50 |
| 11 | Mistral Small 4 | 119B | Apache 2.0 | estimated26 tok/s | 34/50 |
| 12 | GLM-4.7-Flash | 31B | MIT | estimated17 tok/s | 35/50 |
Showing the top 12 of 53 models that fit in 64 GB. See the full leaderboard or all benchmarks.
The fastest way to get started is Ollama. Install it, then find the top pick for your Mac in its library and copy the exact tag it lists:
Find Qwen3.8-27B in the Ollama library → · model card on Hugging Face →
Prefer a GUI? LM Studio gives you a one-click download and chat window. For step-by-step help see our Ollama install guide, or open the Qwen3.8-27B on M2 Max benchmark page for exact settings.
The Mac Studio M2 Max (64 GB) tops out at Mistral Small 4. Newer Apple Silicon with more unified memory runs larger, smarter models much faster:
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Qwen3.8-27B (27.8B, Apache 2.0) is the best all-round pick at 20 tok/s (estimated) on the M2 Max. If you want maximum speed, Maple Preview 20B-A1B hits 346 tok/s (estimated); for maximum capability, Qwen 3.6-27B still fits in 64 GB.
About 53 of the 89 models in the LLMCheck leaderboard fit in 64 GB of unified memory, from compact models up to Mistral Small 4 (119B).
Yes. A 70B model in Q4 quantization needs roughly 40–44 GB of memory, which fits in 64 GB with headroom for context.
64 GB is plenty for local AI — you can run capable 30B–70B-class models. Because Apple Silicon uses unified memory, that figure is both your system RAM and your VRAM.