Can DeepSeek R1 Distill 32B run on NVIDIA B200 180GB?

YES — Runs Great

A72Great

Estimated from fit model

DeepSeek R1 Distill 32B needs ~42.6 GB VRAM. NVIDIA B200 180GB has 180.0 GB. With Q4_K_M quantization, expect ~372 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) — 42.6 GB, 371.8 tok/s, Runs well

42.6 GB required180.0 GB available

24% VRAM used

Fit status

Runs well

Decode

371.8 tok/s

TTFT

521 ms

Safe context

33K

Memory

42.6 GB / 180.0 GB

Memory breakdown

Weights19.5 GB

KV Cache3.9 GB

Runtime1.2 GB

Headroom18.0 GB

See how fast it feels

See how fast it feelsDeepSeek R1 Distill 32B on NVIDIA B200 180GB
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: 371.8 tok/s decode · 521ms TTFT (warm) · 930 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	A	Runs well	344.3 tok/s	350 ms	33K
Coding	A	Runs well	371.8 tok/s	521 ms	33K
Agentic Coding	A	Runs well	371.8 tok/s	757 ms	33K
Reasoning	A	Runs well	371.8 tok/s	615 ms	33K
RAG	A	Runs well	371.8 tok/s	947 ms	33K

Quantization options

How DeepSeek R1 Distill 32B (32B params) fits at each quantization level on NVIDIA B200 180GB (180.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	12.5 GB	Low	B63
Q3_K_S	3	15.7 GB	Low	B63
NVFP4	4

Get started

Copy-paste commands to run DeepSeek R1 Distill 32B on your machine.

Run

ollama run deepseek-r1:32b

Your hardware

More models your NVIDIA B200 180GB can run

Model	Params	Grade	Decode	Capabilities
Devstral 2 123B Instruct	123B	S	97.4 tok/s
Qwen 3.5 122B A10B	122B	S

Frequently asked questions

Can NVIDIA B200 180GB run DeepSeek R1 Distill 32B?

Yes, NVIDIA B200 180GB can run DeepSeek R1 Distill 32B with a A grade (Runs well). Expected decode speed: 371.8 tok/s.

How much VRAM does DeepSeek R1 Distill 32B need?

DeepSeek R1 Distill 32B (32B parameters) requires approximately 42.6 GB of memory with Q4_K_M quantization.

What is the best quantization for DeepSeek R1 Distill 32B?

The recommended quantization for DeepSeek R1 Distill 32B is Q4_K_M, which balances quality and memory efficiency.

What speed will DeepSeek R1 Distill 32B run at on NVIDIA B200 180GB?

On NVIDIA B200 180GB, DeepSeek R1 Distill 32B achieves approximately 371.8 tokens per second decode speed with a time-to-first-token of 521ms using Q4_K_M quantization.

Can NVIDIA B200 180GB run DeepSeek R1 Distill 32B for coding?

For coding workloads, DeepSeek R1 Distill 32B on NVIDIA B200 180GB receives a A grade with 371.8 tok/s and 33K context.

What context window can DeepSeek R1 Distill 32B use on NVIDIA B200 180GB?

On NVIDIA B200 180GB, DeepSeek R1 Distill 32B can safely use up to 33K tokens of context. The model's official context limit is 33K, but available memory constrains the safe maximum.

See all results for NVIDIA B200 180GB See all hardware for DeepSeek R1 Distill 32B

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