Will It Run AI

Can Mistral Small 3.2 24B run on RX 7900 XT 20GB?

YES — With Offload

A84Great
Estimated from fit model

Mistral Small 3.2 24B needs ~20.3 GB VRAM. RX 7900 XT 20GB has 20.0 GB. With Q4_K_M quantization, expect ~26 tok/s.

Runtime: OllamaCapacity: OffloadBandwidth: HighStack: BasicBottleneck: Balanced
Share:

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) 20.3 GB, 25.7 tok/s, Runs with offload (needs ~0.2 GB host RAM)
20.3 GB required20.0 GB available
102% VRAM needed

0.3 GB over capacity — needs offload or smaller quantization

Fit status

Runs with offload (needs ~0.2 GB host RAM)

Decode

25.7 tok/s

TTFT

7542 ms

Safe context

14K

Memory

20.3 GB / 20.0 GB

Memory breakdown

Weights14.6 GB
KV Cache2.4 GB
Runtime1.2 GB
Headroom2.0 GB

See how fast it feels

See how fast it feelsMistral Small 3.2 24B on RX 7900 XT 20GB
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: 25.7 tok/s decode · 7.5s TTFT (warm) · 64 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

Very little memory headroom

You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.

Best improvement path

Buy headroom, not only minimum fit

A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.

Performance by workload

WorkloadGradeFitDecodeTTFTContext
ChatARuns with offload35.2 tok/s2996 ms14K
CodingARuns with offload (needs ~0.2 GB host RAM)25.7 tok/s7542 ms14K
Agentic CodingAVery compromised (needs ~1.8 GB host RAM)20.2 tok/s13936 ms14K
ReasoningARuns with offload (needs ~0.2 GB host RAM)25.7 tok/s8914 ms14K
RAGAVery compromised (needs ~1.8 GB host RAM)20.2 tok/s17420 ms14K

Quantization options

How Mistral Small 3.2 24B (24B params) fits at each quantization level on RX 7900 XT 20GB (20.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
9.4 GB
LowA85
Q3_K_S
3
11.8 GB
LowA84
NVFP4
4
13.4 GB
MediumA84
Q4_K_MBest for your GPU
4
14.6 GB
MediumA84
Q5_K_M
5
17.3 GB
HighF0
Q6_K
6
19.7 GB
HighF0
Q8_0
8
25.7 GB
Very HighF0
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 RX 7900 XT 20GB can run

ModelParamsGradeDecodeCapabilities
AlibabaQwen3-Coder 30B A3B Instruct30.5BA39.6 tok/s
AlibabaQwen 3.5 27B27BA17.8 tok/s
AlibabaQwen 3.6 27B27BS22.1 tok/s
AlibabaQwen3-VL 30B A3B Instruct30BA42.1 tok/s
AlibabaQwen 3 30B A3B30.5BA39.6 tok/s

Frequently asked questions

Can RX 7900 XT 20GB run Mistral Small 3.2 24B?

Yes, RX 7900 XT 20GB can run Mistral Small 3.2 24B with a A grade (Runs with offload (needs ~0.2 GB host RAM)). Expected decode speed: 25.7 tok/s.

How much VRAM does Mistral Small 3.2 24B need?

Mistral Small 3.2 24B (24B parameters) requires approximately 20.3 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 RX 7900 XT 20GB?

On RX 7900 XT 20GB, Mistral Small 3.2 24B achieves approximately 25.7 tokens per second decode speed with a time-to-first-token of 7542ms using Q4_K_M quantization.

Can RX 7900 XT 20GB run Mistral Small 3.2 24B for coding?

For coding workloads, Mistral Small 3.2 24B on RX 7900 XT 20GB receives a A grade with 25.7 tok/s and 14K context.

What context window can Mistral Small 3.2 24B use on RX 7900 XT 20GB?

On RX 7900 XT 20GB, Mistral Small 3.2 24B can safely use up to 14K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

What should I upgrade first if Mistral Small 3.2 24B feels slow on RX 7900 XT 20GB?

Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.

See all results for RX 7900 XT 20GBSee all hardware for Mistral Small 3.2 24B
Embed this result

Paste this snippet into any page to show a live fit card.

<iframe src="https://willitrunai.com/embed/mistral-small-3.2-24b-on-rx-7900-xt-20gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

Preview: