RTX A6000 48GBBudget pick48 GB VRAM (+8)
B
This setup is broadly balanced for this model.42 tok/s decode
~$4,650 MSRP
Mixtral 8x7B needs ~35.8 GB VRAM. NVIDIA A100 40GB has 40.0 GB. With Q4_K_M quantization, expect ~94 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
Tight fit
Decode
94.0 tok/s
TTFT
2061 ms
Safe context
33K
Memory
35.8 GB / 40.0 GB
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Tight fit | 94.0 tok/s | 1124 ms | 33K |
| Coding | B | Tight fit | 94.0 tok/s | 2061 ms | 33K |
| Agentic Coding | B | Tight fit | 94.0 tok/s | 2997 ms | 33K |
| Reasoning | B | Tight fit | 94.0 tok/s | 2435 ms | 33K |
| RAG | B | Tight fit | 94.0 tok/s | 3746 ms | 33K |
How Mixtral 8x7B (47B params) fits at each quantization level on NVIDIA A100 40GB (40.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 18.3 GB | Low | B63 |
Q3_K_S | 3 | 23.0 GB | Low | B64 |
NVFP4 | 4 | 26.3 GB | Medium | B64 |
Q4_K_MBest for your GPU | 4 | 28.7 GB | Medium | B63 |
Q5_K_M | 5 | 33.8 GB | High | F0 |
Q6_K | 6 | 38.5 GB | High | F0 |
Q8_0 | 8 | 50.3 GB | Very High | F0 |
F16 | 16 | 96.4 GB | Maximum | F0 |
Copy-paste commands to run Mixtral 8x7B on your machine.
Run
ollama run mixtralUpgrade options
RTX A6000 48GBBudget pick~$4,650 MSRP
RTX PRO 5000 Blackwell 48GBBest value~$4,999 MSRP
NVIDIA L40 48GBNVIDIA upgrade~$5,500 MSRP
Yes, NVIDIA A100 40GB can run Mixtral 8x7B with a B grade (Tight fit). Expected decode speed: 94.0 tok/s.
Mixtral 8x7B (47B parameters) requires approximately 35.8 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 NVIDIA A100 40GB, Mixtral 8x7B achieves approximately 94.0 tokens per second decode speed with a time-to-first-token of 2061ms using Q4_K_M quantization.
For coding workloads, Mixtral 8x7B on NVIDIA A100 40GB receives a B grade with 94.0 tok/s and 33K context.
On NVIDIA A100 40GB, 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-a100-40gb" 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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