48 GB VRAM (+8)
B
This setup is broadly balanced for this model.42 tok/s decode
~$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 ~87 tok/s.
Runtime: OllamaCapacity: TightBandwidth: HighStack: BasicBottleneck: Balanced
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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 | 87.4 tok/s | 1208 ms | 33K |
| Coding | B | Tight fit | 87.4 tok/s | 2215 ms | 33K |
| Agentic Coding | B | Tight fit | 87.4 tok/s | 3222 ms | 33K |
| Reasoning | B | Tight fit | 87.4 tok/s | 2618 ms | 33K |
| RAG | B | Tight fit | 87.4 tok/s | 4027 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 |
Get started
Copy-paste commands to run Mixtral 8x7B on your machine.
Run
ollama run mixtralUpgrade options