Qwen3 Coder Next
VerifiedOpen-weight LLM built for large-scale code tasks.
About Qwen3 Coder Next
Qwen3 Coder Next follows a transformer architecture optimized for long-context text processing. Its open-weight release allows developers to run and fine-tune the model locally or on private infrastructure without usage restrictions.
The 262k token context enables the model to ingest entire repositories or lengthy technical documents in a single pass. This design supports coherent reasoning across multiple files and extended code histories.
Typical usage includes code completion, refactoring, documentation generation, and debugging within integrated development environments. Teams also deploy it for automated code review and migration projects where large context retention is essential.
Capabilities
How Qwen3 Coder Next compares
Qwen3 Coder Next (striped bar) vs other language models on intelligence, speed and price.
Price
USD per 1M output tokens · Lower is better · Qwen3 Coder Next ranks #37 of 78
Sources: Artificial Analysis (intelligence, speed) · OpenRouter (price).
Best for
Large-scale Codebase Analysis
This model excels at understanding and navigating extensive code repositories thanks to its 262144 token context window, enabling comprehensive reviews without losing track of distant dependencies.
Multi-language Software Development
It supports programming in multiple languages, making it ideal for projects involving polyglot codebases where seamless transitions between languages are required.
Algorithm Optimization and Debugging
The model is well-suited for solving complex algorithmic problems and performing code debugging and refactoring to improve efficiency and maintainability.
Strengths & limitations
Strengths
- +Strong coding specialization
- +Very large context window for codebases
- +Efficient text-only processing
Limitations
- –Text modality only
- –Less general-purpose than full models
- –May hallucinate in complex or novel code scenarios
Cost calculator
Estimate what Qwen3 Coder Next would cost for your usage.
Based on Qwen3 Coder Next's $0.11/1M input · $0.80/1M output. Estimate only — actual cost varies by provider and caching.
Quick start
OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. Only the model slug changes between models.
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://openrouter.ai/api/v1",
apiKey: process.env.OPENROUTER_API_KEY,
});
const completion = await client.chat.completions.create({
model: "qwen/qwen3-coder-next",
messages: [{ role: "user", content: "Hello!" }],
});
console.log(completion.choices[0].message.content);Model slug: qwen/qwen3-coder-next
Editor's verdict
Qwen3 Coder Next is Alibaba Qwen's open-weight language models with a 262K-token context window.
At $0.80 per 1M output tokens, it is very cost-efficient for its class.
As an open-weight model you can self-host it or call it through a hosted API.
Best suited to strong coding specialization and very large context window for codebases.
Frequently asked questions
The model supports a context length of 262144 tokens.
User reviews
Real, verified reviews from the community shape this model's rating.
Loading reviews…
Other Qwen models
Sibling versions in the Qwen family from Alibaba Qwen.
Similar models
Other language models worth comparing.