Can Mistral Small 3.2 24B run on Gaudi 3 128GB?

YES — Runs Great

A81Great

Estimated from fit model

Mistral Small 3.2 24B needs ~31.1 GB VRAM. Gaudi 3 128GB has 128.0 GB. With Q4_K_M quantization, expect ~190 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: HighStack: 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) — 31.1 GB, 190.2 tok/s, Runs well

31.1 GB required128.0 GB available

24% VRAM used

Fit status

Runs well

Decode

190.2 tok/s

TTFT

1018 ms

Safe context

131K

Memory

31.1 GB / 128.0 GB

Memory breakdown

Weights14.6 GB

KV Cache2.4 GB

Runtime1.2 GB

Headroom12.8 GB

See how fast it feels

See how fast it feelsMistral Small 3.2 24B on Gaudi 3 128GB
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: 190.2 tok/s decode · 1.0s TTFT (warm) · 476 tok/s prefill

What limits this setup

The raw memory story may look fine, but the software ecosystem is still a constraint here.

Runtime ecosystem is narrower than CUDA

Intel GPUs can look attractive on memory per dollar, but local AI tooling, kernels, and model coverage are still broader and easier on CUDA today.

Best improvement path

Prefer CUDA if you want the path of least resistance

If your goal is maximum runtime coverage, easier troubleshooting, and better support for new local AI releases, CUDA is usually still the safer upgrade path.

Performance by workload

Workload	Grade	Fit	Decode	TTFT	Context
Chat	A	Runs well	190.2 tok/s	555 ms	131K
Coding	A	Runs well	190.2 tok/s	1018 ms	131K
Agentic Coding	A	Runs well	190.2 tok/s	1481 ms	131K
Reasoning	A	Runs well	190.2 tok/s	1203 ms	131K
RAG	A	Runs well	190.2 tok/s	1851 ms	131K

Quantization options

How Mistral Small 3.2 24B (24B params) fits at each quantization level on Gaudi 3 128GB (128.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	9.4 GB	Low	A72
Q3_K_S	3	11.8 GB	Low	A72
NVFP4	4	13.4 GB	Medium	A73
Q4_K_M	4	14.6 GB	Medium	A73
Q5_K_M	5	17.3 GB	High	A73
Q6_K	6	19.7 GB	High	A73
Q8_0	8	25.7 GB	Very High	A74
F16Best for your GPU	16	49.2 GB	Maximum	A78

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 Gaudi 3 128GB can run

Model	Params	Grade	Decode
Devstral 2 123B Instruct	123B	S	37.5 tok/s
Qwen3-Coder 30B A3B Instruct	30.5B	S	391.6 tok/s
Qwen 3.5 27B	27B	S	169.8 tok/s
Qwen 3.6 27B	27B	S	170.4 tok/s
Qwen 3.5 122B A10B	122B	S	104.1 tok/s

Frequently asked questions

Can Gaudi 3 128GB run Mistral Small 3.2 24B?

Yes, Gaudi 3 128GB can run Mistral Small 3.2 24B with a A grade (Runs well). Expected decode speed: 190.2 tok/s.

How much VRAM does Mistral Small 3.2 24B need?

Mistral Small 3.2 24B (24B parameters) requires approximately 31.1 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 Gaudi 3 128GB?

On Gaudi 3 128GB, Mistral Small 3.2 24B achieves approximately 190.2 tokens per second decode speed with a time-to-first-token of 1018ms using Q4_K_M quantization.

Can Gaudi 3 128GB run Mistral Small 3.2 24B for coding?

For coding workloads, Mistral Small 3.2 24B on Gaudi 3 128GB receives a A grade with 190.2 tok/s and 131K context.

What context window can Mistral Small 3.2 24B use on Gaudi 3 128GB?

On Gaudi 3 128GB, 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.

What should I upgrade first if Mistral Small 3.2 24B feels slow on Gaudi 3 128GB?

Prefer CUDA if you want the path of least resistance. If your goal is maximum runtime coverage, easier troubleshooting, and better support for new local AI releases, CUDA is usually still the safer upgrade path.

Would CUDA be a better path than Gaudi 3 128GB for Mistral Small 3.2 24B?

Often yes, if your goal is the easiest setup and the widest runtime support. Intel can offer attractive memory capacity, but CUDA still tends to win on tooling maturity, guides, kernels, and model coverage for local AI.

See all results for Gaudi 3 128GB See 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-gaudi-3-128gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

Preview:

Workload

Grade

Fit

Decode

TTFT

Context

Chat

Runs well

190.2 tok/s

555 ms

131K

Coding

Runs well

190.2 tok/s

1018 ms

131K

Agentic Coding

Runs well

190.2 tok/s

1481 ms

131K

Reasoning

Runs well

190.2 tok/s

1203 ms

131K

RAG

Runs well

190.2 tok/s

1851 ms

131K

Quantization options

How Mistral Small 3.2 24B (24B params) fits at each quantization level on Gaudi 3 128GB (128.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	9.4 GB	Low	A72
Q3_K_S	3	11.8 GB	Low	A72
NVFP4	4	13.4 GB	Medium	A73
Q4_K_M	4	14.6 GB	Medium	A73
Q5_K_M	5	17.3 GB	High	A73
Q6_K	6	19.7 GB	High	A73
Q8_0	8	25.7 GB	Very High	A74
F16Best for your GPU	16	49.2 GB	Maximum	A78

Model

Params

Grade

Decode

Capabilities

Devstral 2 123B Instruct

123B

37.5 tok/s

Qwen3-Coder 30B A3B Instruct

30.5B

391.6 tok/s

Qwen 3.5 27B

27B

169.8 tok/s

Qwen 3.6 27B

27B

170.4 tok/s

Qwen 3.5 122B A10B

122B

104.1 tok/s

Frequently asked questions

Can Gaudi 3 128GB run Mistral Small 3.2 24B?

Yes, Gaudi 3 128GB can run Mistral Small 3.2 24B with a A grade (Runs well). Expected decode speed: 190.2 tok/s.

How much VRAM does Mistral Small 3.2 24B need?

Mistral Small 3.2 24B (24B parameters) requires approximately 31.1 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 Gaudi 3 128GB?

On Gaudi 3 128GB, Mistral Small 3.2 24B achieves approximately 190.2 tokens per second decode speed with a time-to-first-token of 1018ms using Q4_K_M quantization.

Can Gaudi 3 128GB run Mistral Small 3.2 24B for coding?

For coding workloads, Mistral Small 3.2 24B on Gaudi 3 128GB receives a A grade with 190.2 tok/s and 131K context.

What context window can Mistral Small 3.2 24B use on Gaudi 3 128GB?

On Gaudi 3 128GB, 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.

What should I upgrade first if Mistral Small 3.2 24B feels slow on Gaudi 3 128GB?

Would CUDA be a better path than Gaudi 3 128GB for Mistral Small 3.2 24B?