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URL: https://willitrunai.com/models/deepseek-r1-distill-32b

โ‡ฑ DeepSeek R1 Distill 32B VRAM Requirements โ€” GPU Compatibility


๐Ÿ‘ DeepSeek
DeepSeek

DeepSeek R1 Distill 32B

Frontier
๐Ÿ‘ huggingface
HuggingFace๐Ÿ‘ ollama
Ollama
788.9KDownloads1.6KLikesJan 2025Released33K tokensContextMITLicense61 GoodQuality

DeepSeek R1 Distill 32B (32B parameters) requires approximately 25.2 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 29 GB of VRAM.

Get started

โ€” copy & paste to run locally

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

Run

ollama run deepseek-r1:32b

Quick specs

Parameters32B
Architecturedense
Context33K tokens
Modalitytext
Min RAM12.5 GB
Rec. RAM19.5 GB (Q4_K_M)
LicenseMIT
FamilyDeepSeek
โœ“ Chatโœ“ Reasoning

About this model

We introduce our first-generation reasoning models, DeepSeek-R1-Zero and DeepSeek-R1. DeepSeek-R1-Zero, a model trained via large-scale reinforcement learning (RL) without supervised fine-tuning (SFT) as a preliminary step, demonstrated remarkable performance on reasoning. With RL, DeepSeek-R1-Zero naturally emerged with numerous powerful and interesting reasoning behaviors. However, DeepSeek-R1-Zero encounters challenges such as endless repetition, poor readability, and language mixing.

  • โ€ขWe directly apply reinforcement learning (RL) to the base model without relying on supervised fine-tuning (SFT) as a preliminary step. This...
  • โ€ขWe introduce our pipeline to develop DeepSeek-R1. The pipeline incorporates two RL stages aimed at discovering improved reasoning patterns and...

Related models

Your hardware

Detecting...

Quick picks

Best budgetA
Mac mini M4 64GB~$1,099 โ€” 9 tok/s
๐Ÿ‘ NVIDIA
Best overallA
NVIDIA A100 40GB~$10,000 โ€” 72 tok/s

Best hardware

Top picks for DeepSeek R1 Distill 32B

NVIDIA A100 40GBA
40 GB
RTX PRO 5000 Blackwell 48GBA
48 GB
MacBook Pro M4 Max 64GBA
64 GB
RTX 5090 32GBA
32 GB
RTX 6000 Ada 48GBA
48 GB

Run this model

DeepSeek R1 Distill 32B on NVIDIA A100 40GBDeepSeek R1 Distill 32B on RTX PRO 5000 Blackwell 48GBDeepSeek R1 Distill 32B on MacBook Pro M4 Max 64GB

Quantization options

VRAM estimates by quant level

No hardware detected โ€” fit column shows raw VRAM estimates

QuantBitsVRAMQualityFit
Q2_K
2
12.5 GB
Lowโ€”
Q3_K_S
3
15.7 GB
Lowโ€”
NVFP4
4
17.9 GB
Mediumโ€”
Q4_K_M
4
19.5 GB
Mediumโ€”
Q5_K_M
5
23.0 GB
Highโ€”
Q6_K
6
26.2 GB
Highโ€”
Q8_0
8
34.2 GB
Very Highโ€”
F16
16
65.6 GB
Maximumโ€”

Quality benchmarks

DeepSeek R1 Distill 32B benchmark scores

Benchmark verified

Coding

SWE-bench Verifiedโ€”
HumanEval+โ€”
Aider Polyglotโ€”
LiveCodeBench57.2%

Reasoning

MMLU-Pro41.0%
GPQA Diamond62.1%
MATH-50094.3%
ARC Challengeโ€”

General

Chatbot Arenaโ€”
IFEval41.9%

Source: official ยท 2025-01-20

Hardware compatibility

Fit estimates across all hardware

Open calculator

Computing compatibility...

Memory breakdown

Reference: RTX 2060 6GB

Weights19.5 GB
KV Cache3.9 GB
Runtime1.2 GB
Headroom0.6 GB

Frequently asked questions

FAQ โ€” DeepSeek R1 Distill 32B

See also

Quantization GuideScoring MethodologyVRAM Calculator