Can DeepSeek R1 Distill 32B run on RTX PRO 6000 Blackwell Workstation Edition 96GB?

YES — Runs Great

A75Great
Estimated from fit model

DeepSeek R1 Distill 32B needs ~34.2 GB VRAM. RTX PRO 6000 Blackwell Workstation Edition 96GB has 96.0 GB. With Q4_K_M quantization, expect ~83 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: HighStack: BasicBottleneck: Balanced
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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, 83.3 tok/s, Runs well
34.2 GB required96.0 GB available
36% VRAM used

Fit status

Runs well

Decode

83.3 tok/s

TTFT

2325 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 RTX PRO 6000 Blackwell Workstation Edition 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: 83.3 tok/s decode · 2.3s TTFT (warm) · 208 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

WorkloadGradeFitDecodeTTFTContext
ChatARuns well83.3 tok/s1268 ms33K
CodingARuns well83.3 tok/s2325 ms33K
Agentic CodingARuns well83.3 tok/s3381 ms33K
ReasoningARuns well83.3 tok/s2747 ms33K
RAGARuns well83.3 tok/s4227 ms33K

Inference speed

DeepSeek R1 Distill 32B inference speed — tokens per second by GPU & Mac

Estimated decode speed (tokens/sec) for DeepSeek R1 Distill 32B at Q4_K_M across popular GPUs and Apple Silicon, using the fastest local runtime per device. Fastest is RTX 5090 32GB at ~66 tok/s. Speed is memory-bandwidth bound, so cards that fit the whole model in VRAM run far faster than ones that offload to system RAM.

GPU / MacMemoryQuantSpeed (tok/s)Fits?
NVIDIARTX 5090 32GB
32 GBQ4_K_M66.4Tight
MacBook Pro M4 Max 128GB
128 GBQ4_K_M33.2Fits
MacBook Pro M4 Max 64GB
64 GBQ4_K_M33.2Fits
Mac Studio M3 Ultra 256GB
256 GBQ4_K_M30.8Fits
Mac Studio M2 Ultra 128GB
128 GBQ4_K_M25.7Fits
NVIDIARTX 4090 24GB
24 GBQ4_K_M24.8Heavy offload
Mac Studio M1 Ultra 128GB
128 GBQ4_K_M24.3Fits
RX 7900 XTX 24GB
24 GBQ4_K_M22.9Heavy offload
NVIDIARTX 3090 24GB
24 GBQ4_K_M21.2Heavy offload
MacBook Pro M4 Pro 48GB
48 GBQ4_K_M20.9Tight
MacBook Pro M3 Max 64GB
64 GBQ4_K_M13.3Fits
MacBook Pro M1 Max 64GB
64 GBQ4_K_M12.2Fits
NVIDIARTX 4080 Super 16GB
16 GBQ4_K_M9.0Too big
NVIDIARTX 4070 12GB
12 GBQ4_K_M3.1Too big
NVIDIARTX 3060 12GB
12 GBQ4_K_M2.0Too big
NVIDIARTX 4060 8GB
8 GBQ4_K_M2.0Too big

Estimates for single-stream decoding at Q4_K_M; real tokens/sec varies with prompt length, context, batch size, and runtime build. Prompt processing (prefill) is faster than the decode figures shown here.

Quantization options

How DeepSeek R1 Distill 32B (32B params) fits at each quantization level on RTX PRO 6000 Blackwell Workstation Edition 96GB (96.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
12.5 GB
LowB65
Q3_K_S
3
15.7 GB
LowB65
NVFP4
4
17.9 GB
MediumB66
Q4_K_M
4
19.5 GB
MediumB66
Q5_K_M
5
23.0 GB
HighB66
Q6_K
6
26.2 GB
HighB67
Q8_0
8
34.2 GB
Very HighB69
F16Best for your GPU
16
65.6 GB
MaximumA73

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 RTX PRO 6000 Blackwell Workstation Edition 96GB can run

ModelParamsGradeDecodeCapabilities
MistralDevstral 2 123B Instruct123BS21.8 tok/s
AlibabaQwen 3.5 122B A10B122BS60.5 tok/s
AlibabaQwen 3.6 35B A3B35BS191.3 tok/s
AlibabaQwen 3.5 35B A3B35BS208 tok/s
MistralMistral Small 4 119B119BS65.6 tok/s

Frequently asked questions

Can RTX PRO 6000 Blackwell Workstation Edition 96GB run DeepSeek R1 Distill 32B?

Yes, RTX PRO 6000 Blackwell Workstation Edition 96GB can run DeepSeek R1 Distill 32B with a A grade (Runs well). Expected decode speed: 83.3 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 RTX PRO 6000 Blackwell Workstation Edition 96GB?

On RTX PRO 6000 Blackwell Workstation Edition 96GB, DeepSeek R1 Distill 32B achieves approximately 83.3 tokens per second decode speed with a time-to-first-token of 2325ms using Q4_K_M quantization.

Can RTX PRO 6000 Blackwell Workstation Edition 96GB run DeepSeek R1 Distill 32B for coding?

For coding workloads, DeepSeek R1 Distill 32B on RTX PRO 6000 Blackwell Workstation Edition 96GB receives a A grade with 83.3 tok/s and 33K context.

What context window can DeepSeek R1 Distill 32B use on RTX PRO 6000 Blackwell Workstation Edition 96GB?

On RTX PRO 6000 Blackwell Workstation Edition 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.

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