Can Mixtral 8x7B run on NVIDIA GH200 96GB?

YES — Runs Great

B67Good

Estimated from fit model

Mixtral 8x7B needs ~41.4 GB VRAM. NVIDIA GH200 96GB has 96.0 GB. With Q4_K_M quantization, expect ~233 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: 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.

Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) — 41.4 GB, 233.1 tok/s, Runs well

41.4 GB required96.0 GB available

43% VRAM used

Fit status

Runs well

Decode

233.1 tok/s

TTFT

831 ms

Safe context

33K

Memory

41.4 GB / 96.0 GB

Memory breakdown

Weights28.7 GB

KV Cache2.0 GB

Runtime1.2 GB

Headroom9.6 GB

See how fast it feels

See how fast it feelsMixtral 8x7B on NVIDIA GH200 96GB
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: 233.1 tok/s decode · 831ms TTFT (warm) · 583 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	Runs well	233.1 tok/s	453 ms	33K
Coding	B	Runs well	233.1 tok/s	831 ms	33K
Agentic Coding	B	Runs well	233.1 tok/s	1208 ms	33K
Reasoning	B	Runs well	233.1 tok/s	982 ms	33K
RAG	B	Runs well	233.1 tok/s	1510 ms	33K

Quantization options

How Mixtral 8x7B (47B params) fits at each quantization level on NVIDIA GH200 96GB (96.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	18.3 GB	Low	B56
Q3_K_S	3	23.0 GB	Low	B57
NVFP4	4	26.3 GB	Medium	B57
Q4_K_M	4	28.7 GB	Medium	B58
Q5_K_M	5	33.8 GB	High	B59
Q6_K	6	38.5 GB	High	B60
Q8_0Best for your GPU	8	50.3 GB	Very High	B62
F16	16	96.4 GB	Maximum	F0

Get started

Copy-paste commands to run Mixtral 8x7B on your machine.

Run

ollama run mixtral

Frequently asked questions

Can NVIDIA GH200 96GB run Mixtral 8x7B?

Yes, NVIDIA GH200 96GB can run Mixtral 8x7B with a B grade (Runs well). Expected decode speed: 233.1 tok/s.

How much VRAM does Mixtral 8x7B need?

Mixtral 8x7B (47B parameters) requires approximately 41.4 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 GH200 96GB?

On NVIDIA GH200 96GB, Mixtral 8x7B achieves approximately 233.1 tokens per second decode speed with a time-to-first-token of 831ms using Q4_K_M quantization.

Can NVIDIA GH200 96GB run Mixtral 8x7B for coding?

For coding workloads, Mixtral 8x7B on NVIDIA GH200 96GB receives a B grade with 233.1 tok/s and 33K context.

What context window can Mixtral 8x7B use on NVIDIA GH200 96GB?

On NVIDIA GH200 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.

See all results for NVIDIA GH200 96GB See all hardware for Mixtral 8x7B

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