Mac Studio M3 Ultra 96GB vs Mac Studio M4 Max 64GB
For running models locally, priced in Canada. At 128k context the first runs 37 models fully in memory, the second 30.
In short
The Mac Studio M3 Ultra 96GB has more memory for models: 96 GB against 64 GB. At 128k context the Mac Studio M3 Ultra 96GB runs 37 of the models we track fully in memory and the Mac Studio M4 Max 64GB 30; only the Mac Studio M3 Ultra 96GB holds Qwen3 Coder Next. On the models both run fully in memory, the Mac Studio M3 Ultra 96GB is about 1.5× as fast as the Mac Studio M4 Max 64GB (estimated, median across models).
Updated . Speeds are estimates; how they are worked out.
Specifications
| Spec | Mac Studio M3 Ultra 96GB | Mac Studio M4 Max 64GB |
|---|---|---|
| Chip | Apple M3 Ultra (80-core GPU) | Apple M4 Max (40-core GPU) |
| Memory bus | 1024-bit | 512-bit |
| Memory bandwidth | 819 GB/s | 546 GB/s |
| FP16 compute | 28 TFLOPS | 16.16 TFLOPS |
| Software | Metal | Metal |
| Unified memory | 96 GB | 64 GB |
| GPU can use by default | 72 GB | 48 GB |
| GPU can use, tuned | 88 GB | 56 GB |
| Operating system | macos | macos |
| Processor | M3 Ultra 32-core | M4 Max 16-core |
| Storage | 1000 GB | 1000 GB |
What each runs
Estimated decode speed with the most precise quant that fits each one est.
| Model | Mac Studio M3 Ultra 96GB | Mac Studio M4 Max 64GB |
|---|---|---|
| Qwen 3.8 27B | 14tok/sQ8_0 | 9tok/sQ8_0 |
| Qwen 3.5 122B-A10B | 41tok/sQ3_K_M | 32tok/sUD-Q2_K_XL |
| Qwen 3.6 27B | 14tok/sQ8_0 | 10tok/sQ8_0 |
| Qwen3 Coder Next | 49tok/sQ6_K | won't run |
| Nemotron 3 Super 120B-A12B | 44tok/sUD-Q3_K_M | won't run |
| gpt-oss 120B | 40tok/sMXFP4 | won't run |
| Gemma 4 31B | 12tok/sQ8_0 | 8tok/sQ8_0 |
| Mistral Small 4 119B | 51tok/sUD-Q3_K_M | 40tok/sUD-Q2_K_XL |
| Qwen 3.6 35B-A3B | 55tok/sQ8_0 | 37tok/sQ8_0 |
| Qwen 3.5 27B | 14tok/sQ8_0 | 10tok/sQ8_0 |
| Gemma 4 26B-A4B | 45tok/sQ8_0 | 30tok/sQ8_0 |
| GLM 4.5 Air | 10tok/sQ2_K | won't run |
| Qwen3 Next 80B-A3B | 56tok/sQ6_K | won't run |
| Qwen 3.5 35B-A3B | 55tok/sQ8_0 | 37tok/sQ8_0 |
| GLM 4.7 Flash | 26tok/sQ8_0 | 17tok/sQ8_0 |
| Devstral Small 2 24B | 11tok/sQ8_0 | 8tok/sQ8_0 |
| Nemotron 3.5 Lightning 30B-A3B | 76tok/sUD-Q6_K_XL | 51tok/sUD-Q6_K_XL |
| Kimi Linear 48B-A3B | 75tok/sQ8_0 | 60tok/sQ6_K |
| gpt-oss 20B | 57tok/sMXFP4 | 38tok/sMXFP4 |
| Qwen3 Coder 30B-A3B | 20tok/sQ8_0 | 13tok/sQ8_0 |
| Qwen3 32B | 8tok/sQ8_0 | won't run |
| Gemma 4 12B | 35tok/sQ8_0 | 23tok/sQ8_0 |
| Qwen 3.5 9B | 38tok/sQ8_0 | 26tok/sQ8_0 |
| Gemma 3 27B | 13tok/sQ8_0 | 9tok/sQ8_0 |
| Mistral Small 3.2 24B | 11tok/sQ8_0 | 8tok/sQ8_0 |
| DeepSeek R1 Distill Qwen 32B | 8tok/sQ8_0 | won't run |
| Ministral 3 14B | 15tok/sQ8_0 | 10tok/sQ8_0 |
| Qwen3 14B | 14tok/sQ8_0 | 10tok/sQ8_0 |
| DeepSeek R1 0528 Qwen3 8B | 19tok/sQ8_0 | 13tok/sQ8_0 |
| Qwen3 8B | 19tok/sQ8_0 | 13tok/sQ8_0 |
| Phi-4 14B | 13tok/sQ8_0 | 8tok/sQ8_0 |
| Qwen 3.5 4B | 60tok/sQ8_0 | 40tok/sQ8_0 |
| Ministral 3 8B | 20tok/sQ8_0 | 13tok/sQ8_0 |
| Granite 4.2 8B | 17tok/sQ8_0 | 12tok/sQ8_0 |
| Gemma 4 E4B | 44tok/sQ8_0 | 30tok/sQ8_0 |
| LFM2.5 8B-A1B | 43tok/sQ8_0 | 28tok/sQ8_0 |
| Llama 3.1 8B | 22tok/sQ6_K | 15tok/sQ6_K |
| DeepSeek V4 Flash | won't run | won't run |
| GLM 5.3 Flash | won't run | won't run |
| Qwen 3.8 Flash Next | won't run | won't run |
| MiniMax M2.7 | won't run | won't run |
| Llama 3.3 70B | won't run | won't run |
Questions
- Which is better for local AI, the Mac Studio M3 Ultra 96GB or the Mac Studio M4 Max 64GB?
- Choose the Mac Studio M3 Ultra 96GB to run bigger models. Choose the Mac Studio M3 Ultra 96GB for speed.
- Which can run bigger models, the Mac Studio M3 Ultra 96GB or the Mac Studio M4 Max 64GB?
- At 128k context the Mac Studio M3 Ultra 96GB runs 37 of the models we track fully in memory and the Mac Studio M4 Max 64GB 30; only the Mac Studio M3 Ultra 96GB holds Qwen3 Coder Next.
- Which is faster for local AI, the Mac Studio M3 Ultra 96GB or the Mac Studio M4 Max 64GB?
- On the models both run fully in memory, the Mac Studio M3 Ultra 96GB is about 1.5× as fast as the Mac Studio M4 Max 64GB (estimated, median across models).
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