Can Mixtral 8x22B run on NVIDIA B200 180GB?

YES — Runs Great

B68Good

○Estimated from fit model

Mixtral 8x22B needs ~108.3 GB VRAM. NVIDIA B200 180GB has 180.0 GB. With Q4_K_M quantization, expect ~150 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: HighStack: StandardBottleneck: 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) — 108.3 GB, 162.4 tok/s, Runs well

108.3 GB required180.0 GB available

60% VRAM used

Fit status

Runs well

Decode

162.4 tok/s

TTFT

1192 ms

Safe context

66K

Memory

108.3 GB / 180.0 GB

Memory breakdown

Weights86.0 GB

KV Cache3.4 GB

Runtime0.9 GB

Headroom18.0 GB

See how fast it feels

See how fast it feelsMixtral 8x22B on NVIDIA B200 180GB
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: 162.4 tok/s decode · 1.2s TTFT (warm) · 406 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	149.9 tok/s	705 ms	66K
Coding	B	Runs well	149.9 tok/s	1292 ms	66K
Agentic Coding	B	Runs well	149.9 tok/s	1879 ms	66K
Reasoning	B	Runs well	149.9 tok/s	1527 ms	66K
RAG	B	Runs well	149.9 tok/s	2349 ms	66K

Quantization options

How Mixtral 8x22B (141B params) fits at each quantization level on NVIDIA B200 180GB (180.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	55.0 GB	Low	B56
Q3_K_S	3	69.1 GB	Low	B58
NVFP4	4

Get started

Copy-paste commands to run Mixtral 8x22B on your machine.

Run

ollama run mixtral:8x22b

Frequently asked questions

See all results for NVIDIA B200 180GB See all hardware for Mixtral 8x22B

URL: https://willitrunai.com/can-run/mixtral-8x22b-on-b200-180gb

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