Will It Run AI

Can Mistral Small 3.2 24B run on RTX A6000 48GB?

YES — Runs Great

A84Great
Estimated from fit model

Mistral Small 3.2 24B needs ~23.1 GB VRAM. RTX A6000 48GB has 48.0 GB. With Q4_K_M quantization, expect ~43 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: MediumStack: 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) 23.1 GB, 42.9 tok/s, Runs well
23.1 GB required48.0 GB available
48% VRAM used

Fit status

Runs well

Decode

42.9 tok/s

TTFT

4517 ms

Safe context

131K

Memory

23.1 GB / 48.0 GB

Memory breakdown

Weights14.6 GB
KV Cache2.4 GB
Runtime1.2 GB
Headroom4.8 GB

See how fast it feels

See how fast it feelsMistral Small 3.2 24B on RTX A6000 48GB
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: 42.9 tok/s decode · 4.5s TTFT (warm) · 107 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 well39.9 tok/s2649 ms131K
CodingARuns well42.9 tok/s4517 ms131K
Agentic CodingARuns well42.9 tok/s6570 ms131K
ReasoningARuns well42.9 tok/s5338 ms131K
RAGARuns well42.9 tok/s8213 ms131K

Quantization options

How Mistral Small 3.2 24B (24B params) fits at each quantization level on RTX A6000 48GB (48.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
9.4 GB
LowA77
Q3_K_S
3
11.8 GB
LowA77
NVFP4
4
13.4 GB
MediumA78
Q4_K_M
4
14.6 GB
MediumA78
Q5_K_M
5
17.3 GB
HighA79
Q6_K
6
19.7 GB
HighA80
Q8_0Best for your GPU
8
25.7 GB
Very HighA82
F16
16
49.2 GB
MaximumF0

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 RTX A6000 48GB can run

ModelParamsGradeDecodeCapabilities
AlibabaQwen3-Coder 30B A3B Instruct30.5BS88.3 tok/s
AlibabaQwen 3.5 27B27BS38.3 tok/s
AlibabaQwen 3.6 27B27BS38.4 tok/s
AlibabaQwen 3.6 35B A3B35BS74.2 tok/s
AlibabaQwen3-VL 30B A3B Instruct30BS91.3 tok/s

Frequently asked questions

Can RTX A6000 48GB run Mistral Small 3.2 24B?

Yes, RTX A6000 48GB can run Mistral Small 3.2 24B with a A grade (Runs well). Expected decode speed: 42.9 tok/s.

How much VRAM does Mistral Small 3.2 24B need?

Mistral Small 3.2 24B (24B parameters) requires approximately 23.1 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 RTX A6000 48GB?

On RTX A6000 48GB, Mistral Small 3.2 24B achieves approximately 42.9 tokens per second decode speed with a time-to-first-token of 4517ms using Q4_K_M quantization.

Can RTX A6000 48GB run Mistral Small 3.2 24B for coding?

For coding workloads, Mistral Small 3.2 24B on RTX A6000 48GB receives a A grade with 42.9 tok/s and 131K context.

What context window can Mistral Small 3.2 24B use on RTX A6000 48GB?

On RTX A6000 48GB, 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 RTX A6000 48GBSee all hardware for Mistral Small 3.2 24B
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