Can Mistral Small 3.2 24B run on B100 192GB?

YES — Runs Great

A80Great
Estimated from fit model

Mistral Small 3.2 24B needs ~37.5 GB VRAM. B100 192GB has 192.0 GB. With Q4_K_M quantization, expect ~336 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: 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.

Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) 37.5 GB, 336.0 tok/s, Runs well
37.5 GB required192.0 GB available
20% VRAM used

Fit status

Runs well

Decode

336.0 tok/s

TTFT

576 ms

Safe context

131K

Memory

37.5 GB / 192.0 GB

Memory breakdown

Weights14.6 GB
KV Cache2.4 GB
Runtime1.2 GB
Headroom19.2 GB

See how fast it feels

See how fast it feelsMistral Small 3.2 24B on B100 192GB
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: 336.0 tok/s decode · 576ms TTFT (warm) · 840 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

WorkloadGradeFitDecodeTTFTContext
ChatARuns well336.0 tok/s350 ms131K
CodingARuns well336.0 tok/s576 ms131K
Agentic CodingARuns well336.0 tok/s838 ms131K
ReasoningARuns well336.0 tok/s681 ms131K
RAGARuns well336.0 tok/s1048 ms131K

Quantization options

How Mistral Small 3.2 24B (24B params) fits at each quantization level on B100 192GB (192.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
9.4 GB
LowA71
Q3_K_S
3
11.8 GB
LowA71
NVFP4
4
13.4 GB
MediumA71
Q4_K_M
4
14.6 GB
MediumA71
Q5_K_M
5
17.3 GB
HighA71
Q6_K
6
19.7 GB
HighA71
Q8_0
8
25.7 GB
Very HighA72
F16Best for your GPU
16
49.2 GB
MaximumA75

Get started

Copy-paste commands to run Mistral Small 3.2 24B on your machine.

Run

ollama run mistral-small3.2

Your hardware

More models your B100 192GB can run

ModelParamsGradeDecodeCapabilities
MistralDevstral 2 123B Instruct123BS97.4 tok/s
AlibabaQwen3-Coder 30B A3B Instruct30.5BS1016.1 tok/s
AlibabaQwen 3.5 27B27BS378 tok/s
AlibabaQwen 3.6 27B27BS378 tok/s
AlibabaQwen 3.5 122B A10B122BS270.2 tok/s

Frequently asked questions

Can B100 192GB run Mistral Small 3.2 24B?

Yes, B100 192GB can run Mistral Small 3.2 24B with a A grade (Runs well). Expected decode speed: 336.0 tok/s.

How much VRAM does Mistral Small 3.2 24B need?

Mistral Small 3.2 24B (24B parameters) requires approximately 37.5 GB of memory with Q4_K_M quantization.

What is the best quantization for Mistral Small 3.2 24B?

The recommended quantization for Mistral Small 3.2 24B is Q4_K_M, which balances quality and memory efficiency.

What speed will Mistral Small 3.2 24B run at on B100 192GB?

On B100 192GB, Mistral Small 3.2 24B achieves approximately 336.0 tokens per second decode speed with a time-to-first-token of 576ms using Q4_K_M quantization.

Can B100 192GB run Mistral Small 3.2 24B for coding?

For coding workloads, Mistral Small 3.2 24B on B100 192GB receives a A grade with 336.0 tok/s and 131K context.

What context window can Mistral Small 3.2 24B use on B100 192GB?

On B100 192GB, Mistral Small 3.2 24B can safely use up to 131K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for B100 192GBSee all hardware for Mistral Small 3.2 24B
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