# Qwen3-Coder-Next

Qwen3-Coder-Next is an AI model released by Qwen on Feb 3 2026. It has 80B parameters, a 256k context window and open weight. Tracked results include 70.6% on SWE-Bench Verified, 44.3% on SWE-Bench Pro and 62.8% on SWE-Bench Multilingual.

## Facts

| Field | Value |
| --- | --- |
| Model | Qwen3-Coder-Next |
| Developer | Qwen |
| Release date | Tuesday, Feb 3 2026 |
| Licensing | Open Weight |
| Parameters | 80B |
| Context window | 256k |

## Tracked benchmark scores

| Benchmark | Score | Source | What it measures |
| --- | --- | --- | --- |
| SWE-Bench Pro | 44.3% | Lab | Can the AI fix real bugs in real software? It's handed actual problems from open-source projects and has to write code that genuinely solves them. Higher is better. |
| SWE-Bench Verified | 70.6% | Lab | Real coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better. |
| SWE-Bench Multilingual | 62.8% | Lab | Like SWE-Bench, but the coding problems span many programming languages, not just one. Tests how broadly the AI can code. Higher is better. |
| Terminal-Bench 2.0 | 36.2% | Lab | Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? (Version 2.0 of the test.) Higher is better. |

## About Qwen3-Coder-Next

Qwen3-Coder-Next was released in February 2026 as an open-weight model aimed at coding agents and local development. It used an 80-billion-parameter sparse architecture with about 3 billion active parameters per token and a native 262,144-token context. The training focus included multi-step software work, calling tools and recovering when an attempted execution failed.

The released checkpoint operated in non-thinking mode, so its agent capabilities should not be confused with exposing long reasoning blocks in every response. Alibaba documented integration with several command-line and editor-based agent systems. The model provided a self-hosting option for developers building coding workflows, while the surrounding agent harness still supplied tools, executed commands and managed the interaction with a repository.

## Questions and answers

### When was Qwen3-Coder-Next released?

Qwen3-Coder-Next was released by Qwen on Tuesday, Feb 3 2026.

### Who made Qwen3-Coder-Next?

Qwen3-Coder-Next was built by Qwen. Alibaba's AI lab, building the Qwen family. The most prolific publisher of open-weight models of any major lab, alongside a closed Max and Plus tier sold through Alibaba Cloud.

### What benchmark scores did Qwen3-Coder-Next get?

Qwen3-Coder-Next reports 4 tracked benchmark scores — SWE-Bench Pro: 44.3%; SWE-Bench Verified: 70.6%; SWE-Bench Multilingual: 62.8%; Terminal-Bench 2.0: 36.2%. Tracked scores may come from lab reports or independent benchmarks; source details accompany the benchmark data.

### What is the context window of Qwen3-Coder-Next?

Qwen3-Coder-Next has a context window of 256k. Providers may specify separate input and output token limits.

### How many parameters does Qwen3-Coder-Next have?

Qwen3-Coder-Next is reported at 80B parameters.

### Is Qwen3-Coder-Next open source?

Partly. Qwen3-Coder-Next is an open-weight model: the trained weights are free to download and run locally or on your own infrastructure, but the training data and code are not fully released and the license may restrict some commercial uses. It is not open source in the strict sense.

### What came before and after Qwen3-Coder-Next?

Qwen's previous tracked release was Qwen3-Max on Sep 24 2025, 132 days earlier. It was followed by Qwen3.5 on Feb 16 2026.


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Canonical page: https://aireleasetracker.com/model/qwen/qwen3-coder-next
Site index: https://aireleasetracker.com/llms.txt
Source: AI Release Tracker (https://aireleasetracker.com). Most benchmark scores come from lab launch material; gathered results identify the leaderboard that published them.