The best local LLM for a Mac Studio M4 Max (128 GB) is Qwen 4.1 32B-A3B at 64 tok/s. With 128 GB of unified memory it runs 60 of the models we benchmark — from compact options up to 235B-class models. For everyday chat and coding, Qwen 4.1 32B-A3B is the sweet spot. Full ranking below.
Ranked by LLMCheck suitability (capability balanced against real speed on the M4 Max). Click a model for its full benchmark and setup. Speeds marked est. are scaled from measured runs by memory bandwidth.
| # | Model | Size | License | Speed | Capability |
|---|---|---|---|---|---|
| 1 | Qwen 4.1 32B-A3B | 32B | Apache 2.0 | 64 tok/s | 46/50 |
| 2 | Qwen 4 | 32B | Apache 2.0 | 62 tok/s | 45/50 |
| 3 | Qwen 4 Coder | 32B | Apache 2.0 | 62 tok/s | 44/50 |
| 4 | Qwen 4 Preview 32B-A3B | 32B | Apache 2.0 | 60 tok/s | 42/50 |
| 5 | Qwen3-235B-A22B | 235B | Apache 2.0 | 14 tok/s est. | 46/50 |
| 6 | GLM 5.2 Air | 106B | MIT | 26 tok/s | 40/50 |
| 7 | Qwen 3.6-35B-A3B | 35B | Apache 2.0 | 42 tok/s | 38/50 |
| 8 | Gemma 4 31B | 31B | Apache 2.0 | 18 tok/s | 40/50 |
| 9 | Phi-5 Large 28B | 28B | MIT | 35 tok/s est. | 36/50 |
| 10 | Llama 5 70B | 70B | Llama 5 | 15 tok/s | 38/50 |
| 11 | Gemma 4 26B-A4B | 26B | Apache 2.0 | 40 tok/s | 35/50 |
| 12 | Mistral Medium 4 | 41B | Apache 2.0 | 38 tok/s | 34/50 |
Showing the top 12 of 60 models that fit in 128 GB. See the full leaderboard or all benchmarks.
The fastest way to get started is Ollama. Install it, then pull the top pick for your Mac:
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 Qwen 4.1 32B-A3B on M4 Max benchmark page for exact settings.
The Mac Studio M4 Max (128 GB) comfortably runs 60 of the models we benchmark, led by Qwen 4.1 32B-A3B. Grab one and start running LLMs offline today:
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Qwen 4.1 32B-A3B (32B, Apache 2.0) is the best all-round pick at 64 tok/s on the M4 Max. If you want maximum speed, Gemma 4 E2B hits 141 tok/s; for maximum capability, Qwen3-235B-A22B still fits in 128 GB.
About 60 of the 79 models in the LLMCheck leaderboard fit in 128 GB of unified memory, from compact models up to Qwen3-235B-A22B (235B).
Yes. A 70B model in Q4 quantization needs roughly 40–44 GB of memory, which fits in 128 GB with headroom for context.
128 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.