Macs
Which AI models run on the M2 Ultra (64 GB, 76-core GPU)?
The M2 Ultra (64 GB, 76-core GPU) has 64 GB of memory, about 48 GB of it usable for a model, and 800 GB/s of memory bandwidth. 92 of the 110 models in our catalog run on it at 4-bit or better.
Data as of 2 November 2026 · Vendor specs
64 GBmemory
~48 GB usable for a model
800 GB/sbandwidth, sets the speed
92models run at 4-bit or better
Models that run on it
| Model | Best build | Memory | Speed |
|---|---|---|---|
| Llama 3.3 70B70.6B | Q4_K_M | 44 GB | ~14 tok/s ModelFit est. |
| Llama 3.3 Nemotron Super 49B49B | Q6_K | 42 GB | ~11 tok/s our est. |
| Qwen3.6-35B-A3B35B MoE | Q8_0 | 41 GB | ~99 tok/s ModelFit est. |
| Gemma 4 31B30.7B | Q8_0 | 33 GB | ~17 tok/s ModelFit est. |
| Qwen3-Coder-30B-A3B30.5B MoE | Q8_0 | 34 GB | ~80 tok/s ModelFit est. |
| Nemotron 3 Nano 30B-A3B30B MoE | Q8_0 | 34 GB | ~138 tok/s our est. |
| Qwen3.8-27B27.3B | Q8_0 | 29 GB | ~21 tok/s ModelFit est. |
| Gemma 4 26B-A4B25.2B MoE | Q8_0 | 30 GB | ~76 tok/s ModelFit est. |
| gpt-oss-20b21B MoE | MXFP4 | 15.1 GB | ~103 tok/s ModelFit est. |
| Nemotron Nano 9B v29B | FP16 | 19.4 GB | ~24 tok/s our est. |
| Qwen3.5 9B Instruct9B | Q8_0 | 12.0 GB | ~59 tok/s ModelFit est. |
| Qwen2.5 7B Instruct7B | Q4_K_M | 6.6 GB | ~95 tok/s ModelFit est. |
| Gemma 3 4B Instruct4B | Q8_0 | 5.0 GB | ~98 tok/s ModelFit est. |
| Kolibri 178.1B | IQ4_XS | 46 GB | ~121 tok/s ModelFit est. |
| Llama 3.1 70B Instruct70B | Q4_K_M | 44 GB | ~14 tok/s ModelFit est. |
| DeepSeek-R1 Distill Llama 70B70B | Q4_K_M | 44 GB | ~14 tok/s ModelFit est. |
| Mixtral 8x7B Instruct46.7B MoE | Q4_K_M | 32 GB | ~43 tok/s ModelFit est. |
| Flint 40B-A2.5B39.8B MoE | NVFP4 | 24 GB | ~146 tok/s ModelFit est. |
| Sage-A1.535.95B | Q4_K_M | 23 GB | ~139 tok/s ModelFit est. |
| Qwen3.5 35B-A3B Instruct35B MoE | Q8_0 | 41 GB | ~99 tok/s ModelFit est. |
| Ornith 1.0 35B35B | Q4_K_M | 23 GB | ~141 tok/s ModelFit est. |
| Nanbeige4.3 33B33.1B | Q8_0 | 37 GB | ~17 tok/s ModelFit est. |
| Poolside Laguna XS.233B | Q4_K_M | 25 GB | no estimate |
| Laguna XS 2.133B | Q4_K_M | 22 GB | ~133 tok/s ModelFit est. |
| Qwen3 32B32B | Q8_0 | 37 GB | ~17 tok/s ModelFit est. |
| DeepSeek-R1 Distill Qwen 32B32B | Q8_0 | 37 GB | ~17 tok/s ModelFit est. |
| Olmo 3.1 32B Instruct32B | Q4_K_M | 21 GB | ~28 tok/s ModelFit est. |
| Qwen3 30B30B | Q8_0 | 32 GB | ~80 tok/s ModelFit est. |
| NVIDIA Nemotron Cascade 2 30B-A3B30B MoE | Q6_K | 26 GB | ~183 tok/s our est. |
| Cohere North Mini Code30B | Q4_K_M | 20 GB | no estimate |
| Nemotron 3.5 Lightning 30B-A3B30B MoE | Q4_K_M | 27 GB | ~99 tok/s ModelFit est. |
| GLM-4.7-Flash 30B-A3B30B MoE | Q4_K_M | 20 GB | ~108 tok/s ModelFit est. |
| Granite Switch 4.1 30B30B | Q4_K_M | 23 GB | ~26 tok/s ModelFit est. |
| Muse Glimmer 30B29.8B | Q4_K_M | 18.3 GB | ~34 tok/s ModelFit est. |
| Granite 4.2 30B29.3B | Q4_K_M | 17.9 GB | ~30 tok/s ModelFit est. |
| AREX-2 27B27.4B | Q4_K_M | 18.6 GB | ~33 tok/s ModelFit est. |
| Gemma 2 27B Instruct27B | Q4_K_M | 23 GB | ~31 tok/s ModelFit est. |
| Gemma 3 27B Instruct27B | Q4_K_M | 23 GB | ~32 tok/s ModelFit est. |
| Qwen3.5 27B Instruct27B | Q8_0 | 29 GB | ~21 tok/s ModelFit est. |
| Qwen3.6 27B27B | Q8_0 | 32 GB | ~21 tok/s ModelFit est. |
| Jebadiah 27B27B | Q8_0 | 31 GB | ~21 tok/s ModelFit est. |
| Mistral Small 3.124B | Q8_0 | 25 GB | ~22 tok/s ModelFit est. |
| LFM2 24B-A2B Instruct24B MoE | Q4_K_M | 15.3 GB | ~148 tok/s ModelFit est. |
| Devstral Small 2 24B24B | Q4_K_M | 16.6 GB | ~36 tok/s ModelFit est. |
| Mistral Small 22B22B | Q4_K_M | 18.4 GB | ~40 tok/s ModelFit est. |
| Qwen2.5 14B Instruct14B | Q4_K_M | 12.3 GB | ~55 tok/s ModelFit est. |
| Phi-3 Medium 14B14B | Q4_K_M | 12.3 GB | ~40 tok/s our est. |
| Phi-4 14B14B | Q8_0 | 15.9 GB | ~35 tok/s ModelFit est. |
| Qwen2.5 Coder 14B14B | Q4_K_M | 12.3 GB | ~55 tok/s ModelFit est. |
| Qwen3 14B14B | Q8_0 | 17.3 GB | ~35 tok/s ModelFit est. |
| DeepSeek-R1 Distill Qwen 14B14B | Q8_0 | 16.0 GB | ~35 tok/s ModelFit est. |
| Ministral 3 14B13.5B | Q4_K_M | 10.3 GB | ~55 tok/s ModelFit est. |
| Mellum2.1 12B-A2.5B Thinking12.1B MoE | Q4_K_M | 9.3 GB | ~263 tok/s our est. |
| Mistral Nemo 12B12B | Q8_0 | 13.4 GB | ~41 tok/s ModelFit est. |
| Gemma 3 12B Instruct12B | Q4_K_M | 10.7 GB | ~63 tok/s ModelFit est. |
| Gemma 4 12B12B | Q8_0 | 14.1 GB | ~41 tok/s ModelFit est. |
| GLM-4-9B-Chat9.4B | Q8_0 | 11.2 GB | ~54 tok/s ModelFit est. |
| Gemma 2 9B Instruct9B | Q4_K_M | 8.2 GB | ~67 tok/s ModelFit est. |
| Ornith 1.0 9B9B | Q4_K_M | 6.7 GB | ~88 tok/s ModelFit est. |
| MiMo-V2.6-Distill-Qwen-9B9B | Q4_K_M | 6.9 GB | ~86 tok/s ModelFit est. |
| Jebadiah 9B9B | Q8_0 | 11.0 GB | ~58 tok/s ModelFit est. |
| Granite 4.2 8B8.8B | Q4_K_M | 6.1 GB | ~80 tok/s ModelFit est. |
| Granite Switch 4.1 8B8.8B | Q4_K_M | 7.6 GB | ~68 tok/s ModelFit est. |
| MiniCPM-V 4.5 8B8.7B | Q4_K_M | 6.8 GB | ~86 tok/s ModelFit est. |
| Ministral 3 8B8.4B | Q4_K_M | 7.1 GB | ~76 tok/s ModelFit est. |
| LFM2.5 8B-A1B8.3B MoE | Q4_K_M | 6.6 GB | ~172 tok/s ModelFit est. |
| Llama 3.1 8B Instruct8B | Q8_0 | 9.2 GB | ~59 tok/s ModelFit est. |
| Qwen3 8B8B | Q8_0 | 9.3 GB | ~58 tok/s ModelFit est. |
| Granite 4.1 8B Instruct8B | Q4_K_M | 6.6 GB | ~77 tok/s ModelFit est. |
| Mistral 7B Instruct7B | Q8_0 | 8.4 GB | ~61 tok/s ModelFit est. |
| Qwen2.5 Coder 7B7B | Q4_K_M | 6.6 GB | ~95 tok/s ModelFit est. |
| DeepSeek-R1 Distill Qwen 7B7B | Q8_0 | 8.7 GB | ~64 tok/s ModelFit est. |
| Gemma 4 E4B4.5B | Q8_0 | 8.7 GB | ~88 tok/s ModelFit est. |
| Qwen3.5 4B Instruct4B | Q8_0 | 5.4 GB | ~94 tok/s ModelFit est. |
| NVIDIA Nemotron 3.5 Bolt E4B4B | Q4_K_M | 9.1 GB | ~106 tok/s ModelFit est. |
| Phi-3 Mini 3.8B3.8B | Q4_K_M | 4.3 GB | ~138 tok/s our est. |
| Phi-4 Mini 3.8B3.8B | Q8_0 | 4.9 GB | ~94 tok/s ModelFit est. |
| Granite 4.2 3B3.7B | Q4_K_M | 3.2 GB | ~141 tok/s ModelFit est. |
| Ministral 3 3B3.4B | Q4_K_M | 4.1 GB | ~116 tok/s ModelFit est. |
| Qwen2.5 3B Instruct3B | Q4_K_M | 3.6 GB | ~154 tok/s ModelFit est. |
| Llama 3.2 3B Instruct3B | Q4_K_M | 3.6 GB | ~139 tok/s ModelFit est. |
| Granite 4.1 3B Instruct3B | Q4_K_M | 3.0 GB | ~141 tok/s ModelFit est. |
| Gemma 4 E2B2.3B | Q8_0 | 5.7 GB | ~154 tok/s ModelFit est. |
| Gemma 2 2B Instruct2B | Q4_K_M | 2.8 GB | ~151 tok/s ModelFit est. |
| Qwen3.5 2B Instruct2B | Q4_K_M | 2.8 GB | ~155 tok/s ModelFit est. |
| LFM3 1.7B1.73B | Q4_K_M | 2.1 GB | ~200 tok/s ModelFit est. |
| Qwen2.5 1.5B Instruct1.5B | Q4_K_M | 2.5 GB | ~203 tok/s ModelFit est. |
| Llama 3.2 1B Instruct1B | Q4_K_M | 2.0 GB | ~215 tok/s ModelFit est. |
| Gemma 3 1B Instruct1B | Q8_0 | 2.0 GB | ~204 tok/s ModelFit est. |
| Qwen3.5 0.8B Instruct0.8B | Q4_K_M | 1.8 GB | ~221 tok/s ModelFit est. |
| Qwen2.5 0.5B Instruct0.5B | Q4_K_M | 1.8 GB | ~260 tok/s ModelFit est. |
| SmolLM2 360M0.36B | Q4_K_M | 1.5 GB | ~218 tok/s ModelFit est. |
Speeds come from ModelFit's estimates (CC BY 4.0) where it covers the model, otherwise from our bandwidth formula. Method
Fits only at 3-bit or lower
Too big for this machine
Qwen3-Next 80B-A3B (53 GB), Nemotron 3 Super 120B-A12B (67 GB), gpt-oss-120b (68 GB), Llama 4 Scout (70 GB), Ling-3.0-flash (71 GB), Qwen3.5 122B-A10B Instruct (75 GB), Devstral 2 123B (78 GB), Ornith 1.5 122B (79 GB), Qwen3.8-Flash-Next (93 GB), Laguna S 2.1 (99 GB), Qwen3-235B-A22B (134 GB), DeepSeek-V4-Flash (177 GB) and more.
Questions
What is the best AI model for the M2 Ultra (64 GB, 76-core GPU)?
Llama 3.3 70B at Q4_K_M: the largest model on our shortlist of current models that runs at 4-bit or better at a usable speed (about 14 tok/s, ModelFit est.).
How much memory can a model use on the M2 Ultra (64 GB, 76-core GPU)?
About 48 GB of the 64 GB.
How fast is the M2 Ultra (64 GB, 76-core GPU) for local LLMs?
Decode speed is limited by memory bandwidth: 800 GB/s. A model that reads 10 GB per token runs at under 80 tokens per second.