Can Mistral Small 3.2 24B run on RTX A4500 20GB?

YES — With Offload

A84Great

Estimated from fit model

Mistral Small 3.2 24B needs ~20.3 GB VRAM. RTX A4500 20GB has 20.0 GB. With Q4_K_M quantization, expect ~27 tok/s.

Runtime: OllamaCapacity: OffloadBandwidth: MediumStack: 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) — 20.3 GB, 26.7 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

26.7 tok/s

TTFT

7252 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 RTX A4500 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: 26.7 tok/s decode · 7.3s TTFT (warm) · 67 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

Workload	Grade	Fit	Decode	TTFT	Context
Chat	A	Runs with offload	36.7 tok/s	2881 ms	14K
Coding	A	Runs with offload (needs ~0.2 GB host RAM)	26.7 tok/s	7252 ms	14K
Agentic Coding	A	Very compromised (needs ~1.8 GB host RAM)	21.0 tok/s	13400 ms	14K
Reasoning	A	Runs with offload (needs ~0.2 GB host RAM)	26.7 tok/s	8571 ms	14K
RAG	A	Very compromised (needs ~1.8 GB host RAM)	21.0 tok/s	16750 ms	14K

Quantization options

How Mistral Small 3.2 24B (24B params) fits at each quantization level on RTX A4500 20GB (20.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	9.4 GB	Low	A85
Q3_K_S	3	11.8 GB	Low	A84
NVFP4	4	13.4 GB	Medium	A84
Q4_K_MBest for your GPU	4	14.6 GB	Medium	A84
Q5_K_M	5	17.3 GB	High	F0
Q6_K	6	19.7 GB	High	F0
Q8_0	8	25.7 GB	Very High	F0
F16	16	49.2 GB	Maximum	F0

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 A4500 20GB can run

Model	Params	Grade	Decode
Qwen3-Coder 30B A3B Instruct	30.5B	A	41.2 tok/s
Qwen 3.5 27B	27B	A	18.6 tok/s
Qwen 3.6 27B	27B	S	23 tok/s
Qwen3-VL 30B A3B Instruct	30B	A	43.8 tok/s
Qwen 3 30B A3B	30.5B	A	41.2 tok/s

Frequently asked questions

Can RTX A4500 20GB run Mistral Small 3.2 24B?

Yes, RTX A4500 20GB can run Mistral Small 3.2 24B with a A grade (Runs with offload (needs ~0.2 GB host RAM)). Expected decode speed: 26.7 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 RTX A4500 20GB?

On RTX A4500 20GB, Mistral Small 3.2 24B achieves approximately 26.7 tokens per second decode speed with a time-to-first-token of 7252ms using Q4_K_M quantization.

Can RTX A4500 20GB run Mistral Small 3.2 24B for coding?

For coding workloads, Mistral Small 3.2 24B on RTX A4500 20GB receives a A grade with 26.7 tok/s and 14K context.

What context window can Mistral Small 3.2 24B use on RTX A4500 20GB?

On RTX A4500 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 RTX A4500 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 RTX A4500 20GB See all hardware for Mistral Small 3.2 24B

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