deepseek-ai / text-generation updated 1 year ago

DeepSeek-R1-Distill-Qwen-32B

Name: DeepSeek-R1-Distill-Qwen-32B
Author: deepseek-ai

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 chall...

Params

32.8 B

Context

131,072

Downloads 30d

793 K

Likes

1,584

Commercial use: allowed mit Not gated SAFETENSORS View on Hugging Face ↗

Download history

daily snapshots · 10 days

827 K793 K

Jul 28Jul 31Aug 3Aug 6

Can you run it?

Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.

File	Quant	Size	Est. VRAM	Verdict on RTX 4090 · 24 GB
model.safetensors	bf16	65.5 GB	77.5 GB	❌ Won’t fit
model.safetensors (bf16, full)	bf16 + 128K ctx	65.5 GB	151.2 GB	❌ Won’t fit

Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.

Run it

copy-paste, exact tags checked against the Hub

~ · curl · api/v1

$ curl -s https://aimodelscomparison.com/api/v1/models/deepseek-r1-distill-qwen-32b
{
  "hf_id": "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",
  "params_b": 32.76,
  "context_length": 131072,
  "license": { "id": "mit", "commercial": "yes" },
  "downloads_30d": 792975,
  "vram_estimates": [
    { "quant": "bf16", "gb": 77.5 }
  ],
  "updated_at": "2026-07-28T18:04:03Z"
}

est. VRAM —on RTX 4090 · 24 GBJSON API →

Specifications

Architecture: Qwen2ForCausalLM
Parameters: 32.8 B
Tensor type: BF16
Context length: 131,072
Vocabulary: 152,064
Layers / heads: 64 / 40
Licence: mit
First seen on the Hub: 2025-01-20
Training datasets: undisclosed
Added to our catalog: 2026-07-28

Compare with

Qwen3-8B 16.3 M Qwen3.6-35B-A3B-NVFP4 11.3 M gpt-oss-20b 8.6 M Qwen3-32B 8.3 M dolphin-2.9.1-yi-1.5-34b 4.6 M OTel-2.0-LLM-31B-IT 3.3 M

Appears in

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