Mixtral 8x7B needs ~41.9 GB VRAM. MacBook Pro M2 Max 96GB has 69.1 GB. With Q4_K_M quantization, expect ~16 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
16.7 tok/s
TTFT
11601 ms
Safe context
33K
Memory
41.9 GB / 69.1 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 | 16.7 tok/s | 6328 ms | 33K |
| Coding | B | Runs well | 15.5 tok/s | 12471 ms | 33K |
| Agentic Coding | B | Runs well | 16.7 tok/s | 16875 ms | 33K |
| Reasoning | B | Runs well | 16.7 tok/s | 13711 ms | 33K |
| RAG | B | Runs well | 16.7 tok/s | 21093 ms | 33K |
How Mixtral 8x7B (47B params) fits at each quantization level on MacBook Pro M2 Max 96GB (69.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 18.3 GB | Low | B58 |
Q3_K_S | 3 | 23.0 GB | Low | B59 |
NVFP4 | 4 |
Copy-paste commands to run Mixtral 8x7B on your machine.
Run
ollama run mixtralUpgrade options
RTX PRO 6000 Blackwell Workstation Edition 96GBBudget pickRaises estimated decode speed by about 549%.
Adds memory headroom for longer context windows and future model growth.
~$9,999 MSRP
RTX PRO 6000 Blackwell Server Edition 96GBBest valueRaises estimated decode speed by about 478%.
Adds memory headroom for longer context windows and future model growth.
~$9,999 MSRP
Yes, MacBook Pro M2 Max 96GB can run Mixtral 8x7B with a B grade (Runs well). Expected decode speed: 15.5 tok/s.
Mixtral 8x7B (47B parameters) requires approximately 41.9 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 MacBook Pro M2 Max 96GB, Mixtral 8x7B achieves approximately 15.5 tokens per second decode speed with a time-to-first-token of 12471ms using Q4_K_M quantization.
For coding workloads, Mixtral 8x7B on MacBook Pro M2 Max 96GB receives a B grade with 15.5 tok/s and 33K context.
On MacBook Pro M2 Max 96GB, 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.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/mixtral-8x7b-on-m2-max-96gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
26.3 GB |
| Medium |
| B60 |
Q4_K_M | 4 | 28.7 GB | Medium | B60 |
Q5_K_M | 5 | 33.8 GB | High | B62 |
Q6_K | 6 | 38.5 GB | High | B63 |
Q8_0Best for your GPU | 8 | 50.3 GB | Very High | B63 |
F16 | 16 | 96.4 GB | Maximum | F0 |
Not always. MacBook Pro M2 Max 96GB 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.