DeepSeek-V3 (2025-03-24)

Language DeepSeek Partly verified Released Mar 24, 2025
  • In Input modalities: Text Out Output modalities: Text
  • Tool use
  • Open weights

Prices

1 offering · prices as listed
Alibaba Cloud Model Studio (opens in a new tab) Official Available on this channel since Jan 28, 2026 China · CNY siliconflow/deepseek-v3-0324
Conditions/ 1M tokensInputOutput
Standard ¥2.00¥8.00

Prices from 阿里云百炼:模型价格 (opens in a new tab) (checked Nov 2, 2026)

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

Details

Reasoning
—
Family
deepseek
Model ID

Run locally

Weights: deepseek-ai/DeepSeek-V3-0324
  • Parameters 684.5B
  • Active 51.1B (estimated) · 256 experts, 8 per token
  • Native precision FP8
  • Layers 61
  • KV cache per token 69 KB
  • Config positions 160K (config.json max_position_embeddings)
  • API context 160K (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
Doesn’t fit IQ4_XS (automatic) 8K context
WeightsKV cacheOverheadUsable
Needs
≈ 356.2 GB (weights 338.7 + KV cache 0.5 + overhead 16.9)
Usable
21.6 GB (90% of its memory)
Try
it’s too large for this hardware; see the smallest that runs it below
PrecisionWeightsNeeds at 8KOn your hardwareLongest context
FP8 (native)maker’s file641.3 GB≈ 673.9Doesn’t fit—
Q6_K523.6 GB≈ 550.3Doesn’t fit—
Q5_K_M453.4 GB≈ 476.6Doesn’t fit—
Q5_0438.3 GB≈ 460.7Doesn’t fit—
Q4_K_M387.3 GB≈ 407.2Doesn’t fit—
Q4_0358.6 GB≈ 377.1Doesn’t fit—
IQ4_XS338.7 GB≈ 356.2Doesn’t fit—
Q3_K_Mquality drops311.6 GB≈ 327.7Doesn’t fit—
IQ3_XXSquality drops243.9 GB≈ 256.6Doesn’t fit—
Q2_Kquality drops239.1 GB≈ 251.6Doesn’t fit—
IQ2_XXSquality drops164.2 GB≈ 172.9Doesn’t fit—

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): no single listed machine; about 6 × 80 GB GPUs.

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≈ 10203.9 GBDoesn’t fit your hardware
LoRA≈ 1279.5 GBDoesn’t fit your hardware
QLoRA≈ 363.1 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
  • LMArena Text 1,395

    #102 of 163 listed models · CI 1,391–1,399 · 44,977 votes

  • Epoch AI · GPQA Diamond 67.6%

    #100 of 168 listed models · ±2.68

  • Epoch AI · MATH Level 5 75.5%

    #24 of 64 listed models · ±0.86

  • Epoch AI · OTIS Mock AIME 2024–2025 37.8%

    #116 of 159 listed models · ±6.24

  • LMArena (Arena), leaderboard-dataset on Hugging Face, licensed CC BY 4.0 · License · as of Oct 28, 2026
  • 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
  • EQ-Bench by Samuel J. Paech (eqbench.com; EQ-bench/EQ-bench-site on GitHub), MIT License. · License · as of Oct 28, 2026
  • changes we made
  1. New language model

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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