Qwen: Qwen3 Coder Next
qwen/qwen3-coder-next
Description
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.
How this model compares
Overall covers the full catalog. By plan covers only models available on that tier (same rules as available models in your list). Position on min–average–max. Prices use the higher of prompt or completion per token, shown per 1M tokens.
Price (per 1M tokens)
Min
Max
This model
336 models in this groupPrice (per 1M tokens)
- Min
- $0.04
- Avg
- $12.385886
- Max
- $750.00
This model: $0.80 / 1M tokens
Context length (tokens)
Min
Max
This model
336 models in this groupContext length (tokens)
- Min
- 4,095 tokens
- Avg
- 382,115.467 tokens
- Max
- 10,000,000 tokens
This model: 262,144 tokens
Capabilities
Text → TextContext: 262,144 tokens
Input:
Text
Output:
Text