Can DeepSeek R1 Distill 32B run on NVIDIA H20 96GB?

YES — Runs Great

A75Great

Estimated from fit model

DeepSeek R1 Distill 32B needs ~34.2 GB VRAM. NVIDIA H20 96GB has 96.0 GB. With Q4_K_M quantization, expect ~179 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) — 34.2 GB, 179.3 tok/s, Runs well

34.2 GB required96.0 GB available

36% VRAM used

Fit status

Runs well

Decode

179.3 tok/s

TTFT

1080 ms

Safe context

33K

Memory

34.2 GB / 96.0 GB

Memory breakdown

Weights19.5 GB

KV Cache3.9 GB

Runtime1.2 GB

Headroom9.6 GB

See how fast it feels

See how fast it feelsDeepSeek R1 Distill 32B on NVIDIA H20 96GB
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: 179.3 tok/s decode · 1.1s TTFT (warm) · 448 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	179.3 tok/s	589 ms	33K
Coding	A	Runs well	179.3 tok/s	1080 ms	33K
Agentic Coding	A	Runs well	179.3 tok/s	1571 ms	33K
Reasoning	A	Runs well	179.3 tok/s	1276 ms	33K
RAG	A	Runs well	179.3 tok/s	1964 ms	33K

Quantization options

How DeepSeek R1 Distill 32B (32B params) fits at each quantization level on NVIDIA H20 96GB (96.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	12.5 GB	Low	B65
Q3_K_S	3	15.7 GB	Low	B65
NVFP4	4	17.9 GB	Medium	B66
Q4_K_M	4	19.5 GB	Medium	B66
Q5_K_M	5	23.0 GB	High	B66
Q6_K	6	26.2 GB	High	B67
Q8_0	8	34.2 GB	Very High	B69
F16Best for your GPU	16	65.6 GB	Maximum	A73

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 H20 96GB can run

Model	Params	Grade	Decode
Devstral 2 123B Instruct	123B	S	47 tok/s
Qwen 3.5 122B A10B	122B	S	130.3 tok/s
Qwen 3.6 35B A3B	35B	S	411.7 tok/s
Qwen 3.5 35B A3B	35B	S	447.8 tok/s
Mistral Small 4 119B	119B	S	141.2 tok/s

Frequently asked questions

Can NVIDIA H20 96GB run DeepSeek R1 Distill 32B?

Yes, NVIDIA H20 96GB can run DeepSeek R1 Distill 32B with a A grade (Runs well). Expected decode speed: 179.3 tok/s.

How much VRAM does DeepSeek R1 Distill 32B need?

DeepSeek R1 Distill 32B (32B parameters) requires approximately 34.2 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 H20 96GB?

On NVIDIA H20 96GB, DeepSeek R1 Distill 32B achieves approximately 179.3 tokens per second decode speed with a time-to-first-token of 1080ms using Q4_K_M quantization.

Can NVIDIA H20 96GB run DeepSeek R1 Distill 32B for coding?

For coding workloads, DeepSeek R1 Distill 32B on NVIDIA H20 96GB receives a A grade with 179.3 tok/s and 33K context.

What context window can DeepSeek R1 Distill 32B use on NVIDIA H20 96GB?

On NVIDIA H20 96GB, 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 H20 96GB See all hardware for DeepSeek R1 Distill 32B

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Preview:

Workload

Grade

Fit

Decode

TTFT

Context

Chat

Runs well

179.3 tok/s

589 ms

33K

Coding

Runs well

179.3 tok/s

1080 ms

33K

Agentic Coding

Runs well

179.3 tok/s

1571 ms

33K

Reasoning

Runs well

179.3 tok/s

1276 ms

33K

RAG

Runs well

179.3 tok/s

1964 ms

33K

Quantization options

How DeepSeek R1 Distill 32B (32B params) fits at each quantization level on NVIDIA H20 96GB (96.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	12.5 GB	Low	B65
Q3_K_S	3	15.7 GB	Low	B65
NVFP4	4	17.9 GB	Medium	B66
Q4_K_M	4	19.5 GB	Medium	B66
Q5_K_M	5	23.0 GB	High	B66
Q6_K	6	26.2 GB	High	B67
Q8_0	8	34.2 GB	Very High	B69
F16Best for your GPU	16	65.6 GB	Maximum	A73

Model

Params

Grade

Decode

Capabilities

Devstral 2 123B Instruct

123B

47 tok/s

Qwen 3.5 122B A10B

122B

130.3 tok/s

Qwen 3.6 35B A3B

35B

411.7 tok/s

Qwen 3.5 35B A3B

35B

447.8 tok/s

Mistral Small 4 119B

119B

141.2 tok/s

Frequently asked questions

Can NVIDIA H20 96GB run DeepSeek R1 Distill 32B?

Yes, NVIDIA H20 96GB can run DeepSeek R1 Distill 32B with a A grade (Runs well). Expected decode speed: 179.3 tok/s.

How much VRAM does DeepSeek R1 Distill 32B need?

DeepSeek R1 Distill 32B (32B parameters) requires approximately 34.2 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 H20 96GB?

On NVIDIA H20 96GB, DeepSeek R1 Distill 32B achieves approximately 179.3 tokens per second decode speed with a time-to-first-token of 1080ms using Q4_K_M quantization.

Can NVIDIA H20 96GB run DeepSeek R1 Distill 32B for coding?

For coding workloads, DeepSeek R1 Distill 32B on NVIDIA H20 96GB receives a A grade with 179.3 tok/s and 33K context.

What context window can DeepSeek R1 Distill 32B use on NVIDIA H20 96GB?

On NVIDIA H20 96GB, 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.