RTX A6000 48GB经济之选48 GB VRAM (+8)
B
This setup is broadly balanced for this model.42 tok/s 解码
~$4,650 MSRP
Can Mixtral 8x7B run on NVIDIA A100 40GB?
YES — Tight Fit
B69Good
Estimated from fit model
Mixtral 8x7B needs ~35.8 GB VRAM. NVIDIA A100 40GB has 40.0 GB. With Q4_K_M quantization, expect ~94 tok/s.
Runtime: OllamaCapacity: TightBandwidth: HighStack: BasicBottleneck: Balanced
Operating mode
Choose the run profile you care about
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
Q4_K_M (Medium quality) — 35.8 GB, 94.0 tok/s, Tight fit
35.8 GB required40.0 GB available
89% VRAM used
Fit status
Tight fit
Decode
94.0 tok/s
TTFT
2061 ms
Safe context
33K
Memory
35.8 GB / 40.0 GB
Memory breakdown
Weights28.7 GB
KV Cache2.0 GB
Runtime1.2 GB
Headroom4.0 GB
See how fast it feels
See how fast it feelsMixtral 8x7B on NVIDIA A100 40GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step.
Given information:
- Speed = 60 mph (miles per hour)
- Time = 2.5 hours
Formula: Distance = Speed x Time
Calculation:
Distance = 60 mph x 2.5 h
= 150 miles
The train travels 150 miles.
Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time.
Breakdown:
- First half: 1.25 hours at 60 mph = 75 miles
- Stop: 20 minutes (no distance)
- Second half: 1.25 hours at 60 mph = 75 miles
Total distance: 150 miles (same)
Total time: 2.5 h + 0.33 h = 2.83 hours
Average speed: 150 / 2.83 = 53 mph
The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 94.0 tok/s decode · 2.1s TTFT (warm) · 235 tok/s prefill
What limits this setup
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.
Best improvement path
Performance by 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 |
Quantization options
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 |
Get started
Copy-paste commands to run Mixtral 8x7B on your machine.
Run
ollama run mixtral升级选项
能流畅运行 Mixtral 8x7B 的硬件
Frequently asked questions
Can NVIDIA A100 40GB run Mixtral 8x7B?
Yes, NVIDIA A100 40GB can run Mixtral 8x7B with a B grade (Tight fit). Expected decode speed: 94.0 tok/s.
How much VRAM does Mixtral 8x7B need?
Mixtral 8x7B (47B parameters) requires approximately 35.8 GB of memory with Q4_K_M quantization.
What is the best quantization for Mixtral 8x7B?
The recommended quantization for Mixtral 8x7B is Q4_K_M, which balances quality and memory efficiency.
What speed will Mixtral 8x7B run at on NVIDIA A100 40GB?
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.
Can NVIDIA A100 40GB run Mixtral 8x7B for coding?
For coding workloads, Mixtral 8x7B on NVIDIA A100 40GB receives a B grade with 94.0 tok/s and 33K context.
What context window can Mixtral 8x7B use on NVIDIA A100 40GB?
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.
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<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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