Can Pixtral 12B run on NVIDIA H200 141GB?

YES — Runs Great

B69Good

Estimated from fit model

Pixtral 12B needs ~25.1 GB VRAM. NVIDIA H200 141GB has 141.0 GB. With Q4_K_M quantization, expect ~168 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) — 25.1 GB, 168.0 tok/s, Runs well

25.1 GB required141.0 GB available

18% VRAM used

Fit status

Runs well

Decode

168.0 tok/s

TTFT

1152 ms

Safe context

131K

Memory

25.1 GB / 141.0 GB

Memory breakdown

Weights7.3 GB

KV Cache2.4 GB

Runtime1.2 GB

Headroom14.1 GB

See how fast it feels

See how fast it feelsPixtral 12B on NVIDIA H200 141GB
1st promptCold start — includes initialization
>What is local AI inference?
Local AI inference means running an AI language model directly on your own hardware — your laptop, desktop, or server — instead of sending requests to a remote cloud API.

When you run inference locally the model weights are loaded into your GPU or unified memory. Each token you generate requires reading those weights from memory, so memory bandwidth is the main bottleneck for decode speed.

Key benefits of running locally:
  - Full privacy: your prompts never leave your machine
  - No per-token cost or rate limits
  - Works offline once the model is downloaded
  - Latency depends only on your hardware
2nd promptWarm — model ready, no init overhead
>How much VRAM do I need?
It depends on the model size and quantization level. A rough rule of thumb:

  Model size     Q4 (4-bit)    Q8 (8-bit)    FP16
  7B params      ~4.3 GB       ~7.5 GB       ~14 GB
  13B params     ~7.9 GB       ~13.9 GB      ~26 GB
  70B params     ~42.7 GB      ~74.9 GB      ~140 GB

Most people use 4-bit quantization (Q4_K_M) which gives 90-95% of full quality at a fraction of the memory. A 24 GB GPU can comfortably run most 7B-13B models.
Estimated: 168.0 tok/s decode · 1.2s TTFT (warm) · 420 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

Workload	Grade	Fit	Decode	TTFT	Context
Chat	B	Runs well	168.0 tok/s	629 ms	131K
Coding	B	Runs well	168.0 tok/s	1152 ms	131K
Agentic Coding	B	Runs well	168.0 tok/s	1676 ms	131K
Reasoning	B	Runs well	168.0 tok/s	1362 ms	131K
RAG	B	Runs well	168.0 tok/s	2095 ms	131K

Quantization options

How Pixtral 12B (12B params) fits at each quantization level on NVIDIA H200 141GB (141.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	4.7 GB	Low	B61
Q3_K_S	3	5.9 GB	Low	B61
NVFP4	4	6.7 GB	Medium	B61
Q4_K_M	4	7.3 GB	Medium	B62
Q5_K_M	5	8.6 GB	High	B62
Q6_K	6	9.8 GB	High	B62
Q8_0	8	12.8 GB	Very High	B62
F16Best for your GPU	16	24.6 GB	Maximum	B63

Get started

Copy-paste commands to run Pixtral 12B on your machine.

Run

ollama run pixtral

Upgrade options

Hardware that runs Pixtral 12B well

Mac Studio M3 Ultra 256GBBudget pick

256 GB Unified (+115)

Adds memory headroom for longer context windows and future model growth.81.8 tok/s decode

Adds memory headroom for longer context windows and future model growth.

~$6,999 MSRP

Frequently asked questions

Can NVIDIA H200 141GB run Pixtral 12B?

Yes, NVIDIA H200 141GB can run Pixtral 12B with a B grade (Runs well). Expected decode speed: 168.0 tok/s.

How much VRAM does Pixtral 12B need?

Pixtral 12B (12B parameters) requires approximately 25.1 GB of memory with Q4_K_M quantization.

What is the best quantization for Pixtral 12B?

The recommended quantization for Pixtral 12B is Q4_K_M, which balances quality and memory efficiency.

What speed will Pixtral 12B run at on NVIDIA H200 141GB?

On NVIDIA H200 141GB, Pixtral 12B achieves approximately 168.0 tokens per second decode speed with a time-to-first-token of 1152ms using Q4_K_M quantization.

Can NVIDIA H200 141GB run Pixtral 12B for coding?

For coding workloads, Pixtral 12B on NVIDIA H200 141GB receives a B grade with 168.0 tok/s and 131K context.

What context window can Pixtral 12B use on NVIDIA H200 141GB?

On NVIDIA H200 141GB, Pixtral 12B 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 NVIDIA H200 141GB See all hardware for Pixtral 12B

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<iframe src="https://willitrunai.com/embed/pixtral-12b-on-h200-141gb" 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

168.0 tok/s

629 ms

131K

Coding

Runs well

168.0 tok/s

1152 ms

131K

Agentic Coding

Runs well

168.0 tok/s

1676 ms

131K

Reasoning

Runs well

168.0 tok/s

1362 ms

131K

RAG

Runs well

168.0 tok/s

2095 ms

131K

Quantization options

How Pixtral 12B (12B params) fits at each quantization level on NVIDIA H200 141GB (141.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	4.7 GB	Low	B61
Q3_K_S	3	5.9 GB	Low	B61
NVFP4	4	6.7 GB	Medium	B61
Q4_K_M	4	7.3 GB	Medium	B62
Q5_K_M	5	8.6 GB	High	B62
Q6_K	6	9.8 GB	High	B62
Q8_0	8	12.8 GB	Very High	B62
F16Best for your GPU	16	24.6 GB	Maximum	B63

Frequently asked questions

Can NVIDIA H200 141GB run Pixtral 12B?

Yes, NVIDIA H200 141GB can run Pixtral 12B with a B grade (Runs well). Expected decode speed: 168.0 tok/s.

How much VRAM does Pixtral 12B need?

Pixtral 12B (12B parameters) requires approximately 25.1 GB of memory with Q4_K_M quantization.

What is the best quantization for Pixtral 12B?

The recommended quantization for Pixtral 12B is Q4_K_M, which balances quality and memory efficiency.

What speed will Pixtral 12B run at on NVIDIA H200 141GB?

On NVIDIA H200 141GB, Pixtral 12B achieves approximately 168.0 tokens per second decode speed with a time-to-first-token of 1152ms using Q4_K_M quantization.

Can NVIDIA H200 141GB run Pixtral 12B for coding?

For coding workloads, Pixtral 12B on NVIDIA H200 141GB receives a B grade with 168.0 tok/s and 131K context.

What context window can Pixtral 12B use on NVIDIA H200 141GB?

On NVIDIA H200 141GB, Pixtral 12B can safely use up to 131K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.