Models Model details

Qwen

Qwen: Qwen3 Coder Next

qwen/qwen3-coder-next

Qwen3-Coder-Next is an open-weight causal language model optimized for coding agents and local development workflows. It uses a sparse MoE design with 80B total parameters and only 3B activated per token, delivering performance comparable to models with 10 to 20x higher active compute, which makes it well suited for cost-sensitive, always-on agent deployment. The model is trained with a strong agentic focus and performs reliably on long-horizon coding tasks, complex tool usage, and recovery from execution failures. With a native 256k context window, it integrates cleanly into real-world CLI and IDE environments and adapts well to common agent scaffolds used by modern coding tools. The model operates exclusively in non-thinking mode and does not emit <think> blocks, simplifying integration for production coding agents.

Input
$0.12

/ 1M tokens

Output
$0.8

/ 1M tokens

Context window
262.14K

tokens

Limits

Context

262,144

tokens

Max output

235,929

90% of the context window

Parameters

79,674,391,296

Model facts

Author

Qwen

Tokenizer

Qwen

Modality

Text -> Text

License

Apache-2.0

Created

Feb 4, 2026

Hugging Face

Qwen/Qwen3-Coder-Next

Default generation parameters

temperature

1

top_p

0.95

Publication status

Hugging Face: verifiedLicense: publishedParameter count: published

Modalities

Input · TextOutput · Text

Generation controls

Frequency penaltyLogit biasLogprobsMax tokensPresence penaltyRepetition penaltyResponse formatSeedStopStructured outputsTemperatureTool choiceToolsTop kTop logprobsTop p

Capability scores

0.9
Agentic index

Better than 7% of models compared

36.2
Coding index

Better than 30% of models compared

9.2
Intelligence index

Better than 18% of models compared