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Model components / Fine-tuned / chat models

DeepSeek-Coder-V2-Instruct

DeepSeek

Dedicated coding mixture-of-experts model, instruction-tuned for generation, completion and chat, built on a DeepSeek-V2 checkpoint with six trillion additional code tokens. It ships in a 236B-total variant with 21B active parameters and a 16B Lite variant, supports 338 programming languages and a 128K context.

A 2024-generation coder, superseded by the V3 and V4 lines. The code repository and the weights carry different terms; the openness axis follows the ones on the weights. Verified 2026-08-13 via the model card and the model-license body.

Openness

3 high confidence
3.0
weights
open(downloadable on HF)
data
closed
code
open(MIT, repo code)
model-license
DeepSeek-Model-License(non-OSI

MIT-licensed inference code and downloadable weights under the DeepSeek Model License, with no training corpus released, so this is open weights. The license's Attachment A forbids military, illegal and discriminatory use and requires those terms to propagate to derivatives, but permits commercial use at any scale - a restriction on conduct rather than on commerce, which is why it does not pull the score down to restricted. DeepSeek's pretrained base models are treated the same way on the same license, and the result is consistent with the DeepSeek chat tier, which reaches the same score under plain MIT.

Adoption

3 high confidence
3.0

The family bands on the sum of downloads across its SKUs. The flagship 236B SKU reads 7,143 in the trailing 30 days and the Lite SKU declared alongside it reads 587,824, summing to 594,967, which lands in 100K-1M. The line has been superseded by DeepSeek-V2.5/V3/R1 and by the 2026 coders and the flagship is in real decline, so the band rests on the Lite SKU people actually run.

Capability

3 medium confidence
3.0

GPT-4-Turbo-class open coder at its 2024 release, but a 2024-generation model now mid-tier vs 2026 frontier coders (Qwen3-Coder, DeepSeek-V4, GLM-5.1, Kimi K2.6). HF card defers exact HumanEval/MBPP/SWE-bench numbers to the paper; scored 3 with medium confidence on vendor positioning.

Verified 2026-08-13