DeepSeek-R1-Distill-Qwen-1.5B

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

Prices

0 offerings · prices as listed

No priced offering is listed for this model yet.

Details

Tool use
—
Structured output
—
Family
deepseek-r-distill-qwen

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

  • Parameters 1.8B
  • Dense
  • Native precision BF16
  • Layers 28
  • KV cache per token 28 KB
  • Config positions 128K (config.json max_position_embeddings)
  • API context 125K (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 BF16 (native) (automatic) 8K context 133–200 tok/sOne GPU
WeightsKV cacheOverheadUsable
Needs
≈ 4.0 GB (weights 3.3 (maker’s file) + KV cache 0.2 + overhead 0.5)
Usable
21.6 GB (90% of its memory)
Generation speed
133–200 tok/s
Longest context
125K (the model’s limit)
First token
about 0.06–0.09 s for a 2K prompt
PrecisionWeightsNeeds at 8KOn your hardwareLongest context
BF16 (native)maker’s file3.3 GB≈ 4.0Runs well 133–200 tok/s125K
Q8_01.8 GB≈ 2.5Runs well 237–356 tok/s125K
FP81.7 GB≈ 2.4Runs well 251–376 tok/s125K
Q6_K1.4 GB≈ 2.1Runs well 297–446 tok/s125K
Q5_K_M1.2 GB≈ 1.9Runs well 336–504 tok/s125K
Q5_01.1 GB≈ 1.9Runs well 346–519 tok/s125K
Q4_K_M1.0 GB≈ 1.7Runs well 383–575 tok/s125K
Q4_00.9 GB≈ 1.6Runs well 408–612 tok/s125K
IQ4_XS0.9 GB≈ 1.6Runs well 427–641 tok/s125K
Q3_K_Mquality drops0.8 GB≈ 1.5Runs well 457–685 tok/s125K
IQ3_XXSquality drops0.6 GB≈ 1.4Runs well 551–827 tok/s125K
Q2_Kquality drops0.6 GB≈ 1.3Runs well 559–839 tok/s125K
IQ2_XXSquality drops0.4 GB≈ 1.1Runs well 728–1092 tok/s125K

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 3080; unified memory Apple M5 · 16 GB.

Run commands

vLLM
vllm serve deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B --max-model-len 8192
Memory to fine-tune
Full≈ 28.4 GBDoesn’t fit your hardware
LoRA≈ 5.3 GBFits your hardware
QLoRA≈ 2.9 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 33.6%

    #157 of 168 listed models · ±2.06

  • Epoch AI · OTIS Mock AIME 2024–2025 21.4%

    #124 of 159 listed models · ±5.28

  • 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

No changes recorded yet.

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

Snapshots, the same family and other models from this provider