DeepSeek-R1-Distill-Llama-70B

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

Prices

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No priced offering is listed for this model yet.

Details

Tool use
—
Structured output
—
Licence
llama3.3 license
Family
deepseek-r-distill-llama

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

  • Parameters 70.6B
  • Dense
  • Native precision BF16
  • Layers 80
  • KV cache per token 320 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
Needs system memory IQ4_XS (automatic) 8K context 2–3 tok/s41/80 layers in system memory
WeightsKV cacheOverheadIn system memoryUsable
Needs
≈ 39.2 GB (weights 34.9 + KV cache 2.5 + overhead 1.7)
Usable
21.6 GB (90% of its memory)
In system memory
17.9 GB · 39/80 layers on the GPU (--n-gpu-layers 39)
Generation speed
2–3 tok/s
First token
about 2.28–3.42 s for a 2K prompt
PrecisionWeightsNeeds at 8KOn your hardwareLongest context
BF16 (native)maker’s file131.4 GB≈ 140.5Doesn’t fit—
Q8_069.8 GB≈ 75.8Doesn’t fit—
FP865.7 GB≈ 71.5Doesn’t fit—
Q6_K54.0 GB≈ 59.2Doesn’t fit—
Q5_K_M46.7 GB≈ 51.6Doesn’t fit—
Q5_045.2 GB≈ 49.9Doesn’t fit—
Q4_K_M39.9 GB≈ 44.4Needs system memory 2–3 tok/s—
Q4_037.0 GB≈ 41.3Needs system memory 2–3 tok/s—
IQ4_XS34.9 GB≈ 39.2Needs system memory 2–3 tok/s—
Q3_K_Mquality drops32.1 GB≈ 36.2Needs system memory 3–4 tok/s—
IQ3_XXSquality drops25.1 GB≈ 28.9Needs system memory 5–7 tok/s—
Q2_Kquality drops24.6 GB≈ 28.4Needs system memory 5–7 tok/s—
IQ2_XXSquality drops16.9 GB≈ 20.3Runs well 24–36 tok/s12K

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 NVIDIA H100 SXM; unified memory Apple M5 Max (40-core GPU) · 64 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≈ 1055.8 GBDoesn’t fit your hardware
LoRA≈ 136.9 GBDoesn’t fit your hardware
QLoRA≈ 42.4 GBDoesn’t fit 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 55.7%

    #117 of 168 listed models · ±2.97

  • Epoch AI · MATH Level 5 89.9%

    #14 of 64 listed models · ±0.68

  • Epoch AI · OTIS Mock AIME 2024–2025 51.4%

    #111 of 159 listed models · ±6.05

  • Epoch AI, 'Capabilities & benchmarking'. Published online at epoch.ai. Retrieved from 'https://epoch.ai/benchmarks'. Licensed CC BY 4.0. · License · as of Oct 18 – 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

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