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URL: https://willitrunai.com/models/deepseek-r1-distill-14b

โ‡ฑ DeepSeek R1 Distill 14B VRAM Requirements โ€” GPU Compatibility


๐Ÿ‘ DeepSeek
DeepSeek

DeepSeek R1 Distill 14B

Frontier
๐Ÿ‘ huggingface
HuggingFace๐Ÿ‘ ollama
Ollama
536.7KDownloads657LikesJan 2025Released33K tokensContextMITLicense59 GoodQuality

DeepSeek R1 Distill 14B (14B parameters) requires approximately 13.3 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 16 GB of VRAM.

Get started

โ€” copy & paste to run locally

Copy-paste commands to run DeepSeek R1 Distill 14B on your machine.

Run

ollama run deepseek-r1

Quick specs

Parameters14B
Architecturedense
Context33K tokens
Modalitytext
Min RAM5.5 GB
Rec. RAM8.5 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
RX 7600 XT 16GB~$329 โ€” 21 tok/s
๐Ÿ‘ NVIDIA
Best overallA
RTX A4500 20GB~$2,000 โ€” 63 tok/s

Best hardware

Top picks for DeepSeek R1 Distill 14B

RTX A4500 20GBA
20 GB
RX 7900 XT 20GBA
20 GB
RTX 4090 24GBA
24 GB
NVIDIA A30 24GBA
24 GB
RTX 5090 Laptop 24GBA
24 GB

Run this model

DeepSeek R1 Distill 14B on RTX A4500 20GBDeepSeek R1 Distill 14B on RX 7900 XT 20GBDeepSeek R1 Distill 14B on RTX 4090 24GB

Quantization options

VRAM estimates by quant level

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

QuantBitsVRAMQualityFit
Q2_K
2
5.5 GB
Lowโ€”
Q3_K_S
3
6.9 GB
Lowโ€”
NVFP4
4
7.8 GB
Mediumโ€”
Q4_K_M
4
8.5 GB
Mediumโ€”
Q5_K_M
5
10.1 GB
Highโ€”
Q6_K
6
11.5 GB
Highโ€”
Q8_0
8
15.0 GB
Very Highโ€”
F16
16
28.7 GB
Maximumโ€”

Quality benchmarks

DeepSeek R1 Distill 14B benchmark scores

Benchmark verified

Coding

SWE-bench Verifiedโ€”
HumanEval+โ€”
Aider Polyglotโ€”
LiveCodeBench53.1%

Reasoning

MMLU-Pro40.7%
GPQA Diamond59.1%
MATH-50093.9%
ARC Challengeโ€”

General

Chatbot Arenaโ€”
IFEval43.8%

Source: official ยท 2025-01-20

Hardware compatibility

Fit estimates across all hardware

Open calculator

Computing compatibility...

Memory breakdown

Reference: RTX 2060 6GB

Weights8.5 GB
KV Cache2.9 GB
Runtime1.2 GB
Headroom0.6 GB

Frequently asked questions

FAQ โ€” DeepSeek R1 Distill 14B

See also

Quantization GuideScoring MethodologyVRAM Calculator