DeepSeek-R1-Distill-Qwen-32B

Language DeepSeek Partly verified Released Feb 5, 2025
  • In Input modalities: Text Out Output modalities: Text
  • Reasoning
  • Open weights

Prices

2 offerings · prices as listed
Alibaba Cloud Model Studio (opens in a new tab) Official Available on this channel since Feb 5, 2025 China · CNY Context: 32.77KReasoning: YesTool use: —Structured output: —Max output: 16.38KInput modalities: TextOutput modalities: TextMax input: 32.77KBuilt-in tools: Web search deepseek-r1-distill-qwen-32b
Conditions/ 1M tokensInputOutput
Standard no longer listed since Oct 11, 2026 ¥2.00¥6.00

Prices from 阿里云百炼:模型价格 (opens in a new tab) (checked Oct 8, 2026)

Standard: the price a request with no conditions pays (the headline price elsewhere on the site).

Details

Tool use
—
Structured output
—
Built-in tools
Web search
Family
deepseek-r-distill-qwen
Model ID

Not stated on DeepSeek’s pages: max input, reasoning efforts, reasoning can be off, max thinking budget, knowledge cutoff, aliases.

  • Parameters 32.8B
  • Dense
  • Native precision BF16
  • Layers 64
  • KV cache per token 256 KB
  • Config positions 128K (config.json max_position_embeddings)
  • API context 32K (maker’s API)
My hardware GeForce RTX 4090 24 GB · 1008 GB/s · 64 GB DDR5 dual channel · 89.6 GB/s
On your hardware · GeForce RTX 4090
Runs well IQ4_XS (automatic) 8K context 26–39 tok/sOne GPU
WeightsKV cacheOverheadUsable
Needs
≈ 19.0 GB (weights 16.2 + KV cache 2.0 + overhead 0.8)
Usable
21.6 GB (90% of its memory)
Generation speed
26–39 tok/s
Longest context
18K (longer doesn’t fit)
First token
about 1.06–1.59 s for a 2K prompt
PrecisionWeightsNeeds at 8KOn your hardwareLongest context
BF16 (native)maker’s file61.0 GB≈ 66.1Doesn’t fit—
Q8_032.4 GB≈ 36.0Needs system memory 3–4 tok/s—
FP830.5 GB≈ 34.0Needs system memory 3–4 tok/s—
Q6_K25.1 GB≈ 28.3Needs system memory 5–7 tok/s—
Q5_K_M21.7 GB≈ 24.8Needs system memory 8–12 tok/s—
Q5_021.0 GB≈ 24.0Needs system memory 10–15 tok/s—
Q4_K_M18.5 GB≈ 21.5Runs well 23–34 tok/s8K
Q4_017.2 GB≈ 20.0Runs well 24–37 tok/s14K
IQ4_XS16.2 GB≈ 19.0Runs well 26–39 tok/s18K
Q3_K_Mquality drops14.9 GB≈ 17.7Runs well 28–42 tok/s23K
IQ3_XXSquality drops11.7 GB≈ 14.3Runs well 34–51 tok/s32K
Q2_Kquality drops11.4 GB≈ 14.0Runs well 35–52 tok/s32K
IQ2_XXSquality drops7.9 GB≈ 10.4Runs well 48–71 tok/s32K

Click a row to choose a precision. “Maker’s file” sizes are the maker’s own files; others are parameters × bits per weight.

Compared with other hardware

Each at the highest precision it runs. Click one for details.

Smallest that runs it (Q4_K_M, 8K): GPU GeForce RTX 4090; unified memory Apple M5 Max (32-core GPU) · 36 GB.

Run commands

The maker publishes no files at this precision. Choose its native precision or one of its own builds, or quantise it yourself with llama.cpp.

Memory to fine-tune
Full≈ 491.5 GBDoesn’t fit your hardware
LoRA≈ 64.8 GBDoesn’t fit your hardware
QLoRA≈ 20.9 GBFits your hardware

Batch 1, 2,048-token sequences, gradient checkpointing; LoRA and QLoRA train rank-16 adapters on the attention projections.

Estimates; facts from the maker’s Hugging Face repositories, as of 2026-11-06. How it’s estimated

Cited scores

From third-party leaderboards, not measured by us
  • Epoch AI · GPQA Diamond 64.1%

    #106 of 168 listed models · ±2.75

  • Epoch AI · OTIS Mock AIME 2024–2025 55.6%

    #108 of 159 listed models · ±6.2

  • Epoch AI, 'Capabilities & benchmarking'. Published online at epoch.ai. Retrieved from 'https://epoch.ai/benchmarks'. Licensed CC BY 4.0. · License · as of Nov 4, 2026
  • changes we made
  1. Now priced on Cloudflare Workers AI Input $0.497 · Output $4.881
  2. Now priced on Alibaba Cloud Model Studio, China Input ¥2.00 · Output ¥6.00
  3. Context window 128K → 32.77K

Sources

DeepSeek’s official policies: data use, privacy, terms →

Some values on this page are still waiting to be checked against official pages: a filled dot is verified, a hollow one is not yet (with or without a source on file). How we verify data

DeepSeek · China · deepseek.com

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