LLMQwenMIT

DeepSeek R1 Distill Qwen 7B

deepseek-ai/DeepSeek-R1-Distill-Qwen-7B

Parameters

7.6B

Context

128K

Downloads

250.4K

Likes

870

Architecture

transformer

View on HuggingFace

GPU Requirements

VRAM / RAM / disk estimates by quantization and usage scenario

QuantizationMinimumRecommendedProduction
FP1616bit
22.9 GB
RAM 34.3 · Disk 61.1
39.4 GB
RAM 59.1 · Disk 87.1
137.1 GB
RAM 205.7 · Disk 126.1
FP88bit
13.9 GB
RAM 32.0 · Disk 50.0
30.1 GB
RAM 45.1 · Disk 76.0
127.4 GB
RAM 191.1 · Disk 115.0
INT88bit
13.9 GB
RAM 32.0 · Disk 50.0
30.1 GB
RAM 45.1 · Disk 76.0
127.4 GB
RAM 191.1 · Disk 115.0
AWQ4bit
9.6 GB
RAM 32.0 · Disk 44.7
25.6 GB
RAM 38.3 · Disk 70.7
122.7 GB
RAM 184.0 · Disk 109.7
GPTQ4bit
9.7 GB
RAM 32.0 · Disk 44.8
25.6 GB
RAM 38.4 · Disk 70.8
122.7 GB
RAM 184.1 · Disk 109.8
GGUF4bit
9.8 GB
RAM 32.0 · Disk 44.9
25.7 GB
RAM 38.6 · Disk 70.9
122.9 GB
RAM 184.3 · Disk 109.9

GPU Recommendations

Best ValueBEST

1× RTX 5090

32 GB VRAM

$246/mo

≈ 488.3 tok/s

Effective production throughput ≈ 341.8 tok/s

score 0.6847

Deploy on vast ↗
Cheapest

2× Tesla V100

32 GB VRAM

$42.2/mo

≈ 0 tok/s (N/A — benchmark unavailable)

Effective production throughput ≈ 0 tok/s

score 0.6336

Deploy on vast ↗
Performance

8× H200 SXM

1128 GB VRAM

$20,440/mo

≈ 4185.3 tok/s

Effective production throughput ≈ 2929.7 tok/s

score 0.2197

Min Complexity

1× RTX A6000

48 GB VRAM

$210/mo

≈ 209.3 tok/s

Effective production throughput ≈ 146.5 tok/s

score 0.6331

Deploy on vast ↗

💬 Community — real deployment experience

0 Articles · 0 Benchmarks

View Community →

GPUs that fit (single card)

RTX A6000

48 GB VRAM

$210

/mo · vast

RTX 5090

32 GB VRAM

$246

/mo · vast

L40S

48 GB VRAM

$341

/mo · vast

RTX PRO 6000 S

48 GB VRAM

$633

/mo · vast

RTX PRO 6000 WS

48 GB VRAM

$634

/mo · vast

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