Mixtral 8x7B needs ~59.2 GB VRAM. Mac Studio M3 Ultra 256GB has 184.3 GB. With Q4_K_M quantization, expect ~37 tok/s.
Operating mode
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
Fit status
Runs well
Decode
40.1 tok/s
TTFT
4833 ms
Safe context
33K
Memory
59.2 GB / 184.3 GB
This setup is broadly balanced for this model.
Shared-memory contention still exists
The OS, browser, and inference runtime all compete for the same physical memory pool, so real-world headroom is less forgiving than raw capacity suggests.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs well | 37.3 tok/s | 2834 ms | 33K |
| Coding | B | Runs well | 37.3 tok/s | 5195 ms | 33K |
| Agentic Coding | B | Runs well | 37.3 tok/s | 7557 ms | 33K |
| Reasoning | B | Runs well | 37.3 tok/s | 6140 ms | 33K |
| RAG | B | Runs well | 37.3 tok/s | 9446 ms | 33K |
How Mixtral 8x7B (47B params) fits at each quantization level on Mac Studio M3 Ultra 256GB (184.3 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 18.3 GB | Low | C53 |
Q3_K_S | 3 | 23.0 GB | Low | C53 |
NVFP4 | 4 | 26.3 GB | Medium | C54 |
Q4_K_M | 4 | 28.7 GB | Medium | C54 |
Q5_K_M | 5 | 33.8 GB | High | C55 |
Q6_K | 6 | 38.5 GB | High | B55 |
Q8_0 | 8 | 50.3 GB | Very High | B57 |
F16Best for your GPU | 16 | 96.4 GB | Maximum | B62 |
Copy-paste commands to run Mixtral 8x7B on your machine.
Run
ollama run mixtralUpgrade-Optionen
Raises estimated decode speed by about 948%.
Adds memory headroom for longer context windows and future model growth.
ca. $8,000 MSRP
Raises estimated decode speed by about 642%.
ca. $15,000 MSRP
Yes, Mac Studio M3 Ultra 256GB can run Mixtral 8x7B with a B grade (Runs well). Expected decode speed: 37.3 tok/s.
Mixtral 8x7B (47B parameters) requires approximately 59.2 GB of memory with Q4_K_M quantization.
The recommended quantization for Mixtral 8x7B is Q4_K_M, which balances quality and memory efficiency.
On Mac Studio M3 Ultra 256GB, Mixtral 8x7B achieves approximately 37.3 tokens per second decode speed with a time-to-first-token of 5195ms using Q4_K_M quantization.
For coding workloads, Mixtral 8x7B on Mac Studio M3 Ultra 256GB receives a B grade with 37.3 tok/s and 33K context.
On Mac Studio M3 Ultra 256GB, Mixtral 8x7B can safely use up to 33K tokens of context. The model's official context limit is 33K, but available memory constrains the safe maximum.
Not always. Mac Studio M3 Ultra 256GB can often fit larger models thanks to unified memory, but a discrete GPU with dedicated high-bandwidth VRAM may still decode faster once the model fits. For this combination, the important distinction is capacity versus sustained throughput.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/mixtral-8x7b-on-m3-ultra-256gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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