The best local LLM for a MacBook Pro M3 Max (128 GB) is DeepSeek V4 Flash at 27 tok/s. With 128 GB of unified memory it runs 58 of the models we benchmark — from compact options up to 284B-class models. For everyday chat and coding, DeepSeek V4 Flash is the sweet spot. Full ranking below.
Ranked by LLMCheck suitability (capability balanced against speed on the M3 Max). Click a model for its full benchmark and setup. All speeds are index estimates (memory-bandwidth model, cross-referenced with sourced benchmarks where available) — submit a real run →
| # | Model | Size | License | Speed | Capability |
|---|---|---|---|---|---|
| 1 | DeepSeek V4 Flash | 284B | MIT | 27 tok/s | 47/50 |
| 2 | Inkling-Small | 276B | Apache 2.0 | 15 tok/s est. | 46/50 |
| 3 | Qwen 3.6-27B | 27B | Apache 2.0 | 27 tok/s | 44/50 |
| 4 | Qwen3-235B-A22B | 235B | Apache 2.0 | 10 tok/s est. | 46/50 |
| 5 | Laguna S 2.1 | 118B | OpenMDW | 17 tok/s est. | 43/50 |
| 6 | Muse Glimmer 30B | 30B | Apache 2.0 | 18 tok/s est. | 42/50 |
| 7 | KAT-Coder-V2.5 | 35B | Apache 2.0 | 35 tok/s est. | 39/50 |
| 8 | Qwen 3.6-35B-A3B | 35B | Apache 2.0 | 35 tok/s est. | 38/50 |
| 9 | Gemma 4 31B | 31B | Apache 2.0 | 16 tok/s est. | 40/50 |
| 10 | Nemotron 3.5 Lightning | 30B | OpenMDW | 40 tok/s est. | 36/50 |
| 11 | Gemma 4 26B-A4B | 26B | Apache 2.0 | 32 tok/s est. | 35/50 |
| 12 | GLM-4.7-Flash | 31B | MIT | 23 tok/s est. | 35/50 |
Showing the top 12 of 58 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 DeepSeek V4 Flash on M3 Max benchmark page for exact settings.
The MacBook Pro M3 Max (128 GB) tops out at DeepSeek V4 Flash. Newer Apple Silicon with more unified memory runs larger, smarter models much faster:
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DeepSeek V4 Flash (284B, MIT) is the best all-round pick at 27 tok/s on the M3 Max. If you want maximum speed, Maple Preview 20B-A1B hits 187 tok/s; for maximum capability, Inkling-Small still fits in 128 GB.
About 58 of the 80 models in the LLMCheck leaderboard fit in 128 GB of unified memory, from compact models up to DeepSeek V4 Flash (284B).
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.