The best local LLM for a Mac Studio M1 Ultra (64 GB) is KAT-Coder-V2.5 at 130 tok/s (estimated). With 64 GB of unified memory it runs 55 of the models in the LLMCheck index — from compact options up to 119B-class models. For everyday chat and coding, KAT-Coder-V2.5 is the sweet spot. Full ranking below.
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Ranked by LLMCheck suitability (capability balanced against speed on the M1 Ultra). 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 | KAT-Coder-V2.5 | 35B | Apache 2.0 | estimated130 tok/s | 39/50 |
| 2 | Qwen 3.6-35B-A3B | 35B | Apache 2.0 | estimated138 tok/s | 38/50 |
| 3 | Qwen3.8-27B | 27.8B | Apache 2.0 | estimated39 tok/s | 46/50 |
| 4 | Nemotron 3.5 Lightning | 30B | OpenMDW | estimated116 tok/s | 36/50 |
| 5 | Gemma 4 26B-A4B | 26B | Apache 2.0 | estimated119 tok/s | 35/50 |
| 6 | Qwen 3.6-27B | 27B | Apache 2.0 | estimated38 tok/s | 44/50 |
| 7 | Laguna XS 2.1 | 33B | OpenMDW | estimated130 tok/s | 33/50 |
| 8 | Qwen3-Coder-Next | 80B | Apache 2.0 | estimated101 tok/s | 35/50 |
| 9 | Muse Glimmer 30B | 30B | Apache 2.0 | estimated35 tok/s | 42/50 |
| 10 | Nemotron-Cascade 2 | 30B | NVIDIA Open | estimated130 tok/s | 30/50 |
| 11 | Gemma 4 31B | 31B | Apache 2.0 | estimated33 tok/s | 40/50 |
| 12 | Qwen 3.5 35B-A3B | 35B | Apache 2.0 | estimated130 tok/s | 27/50 |
Showing the top 12 of 55 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 KAT-Coder-V2.5 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 KAT-Coder-V2.5 on M1 Ultra benchmark page for exact settings.
The Mac Studio M1 Ultra (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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KAT-Coder-V2.5 (35B, Apache 2.0) is the best all-round pick at 130 tok/s (estimated) on the M1 Ultra. If you want maximum speed, Maple Preview 20B-A1B hits 441 tok/s (estimated); for maximum capability, Qwen3.8-27B still fits in 64 GB.
About 55 of the 91 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.