Qwen3-Coder is an advanced AI model specialized in text-to-text coding and programming tasks, designed to support integration and handle complex workflows with a very large context window of 262K tokens.
The evaluation presents the performance of various AI models across different agentic tasks, including coding, browser navigation, and tool usage. It features models like Open3-Coder, DeepSeek-V3, as well as proprietary ones such as Claude and GPT-4.1. Performance is measured through established benchmarks like SWE-bench, WebArena, and BECL-v3, reflecting each model’s proficiency in problem-solving, code generation, and interacting with external tools. The scores reveal distinct strengths: some models outperform others in specialized tasks such as coding accuracy or browser-based problem-solving, while a few demonstrate consistently strong, well-rounded capabilities across multiple benchmarks.
Although Qwen3-Coder offers exceptional agentic capabilities and long-context handling, its complexity and resource demands are high, and it requires specialized infrastructure for deployment. Like other large agentic coding models, it may still face challenges with extremely novel or ambiguous coding tasks and benefits from integration with human oversight for safety and correctness.
Accessible via AI/ML API. Documentation: available here.
Measured on the AI/ML API gateway across live traffic. Figures are medians unless stated. Last updated 2026-10-12.
import requests r = requests.post( "https://api.aimlapi.com/v1/chat/completions", headers={"Authorization": "Bearer " + AIMLAPI_KEY}, json={ "model": "alibaba/qwen3-coder-480b-a35b-instruct", "messages": [ { "role": "user", "content": "Hello!" } ] }, ) print(r.json())
const r = await fetch("https://api.aimlapi.com/v1/chat/completions", { method: "POST", headers: { Authorization: `Bearer ${process.env.AIMLAPI_KEY}`, "Content-Type": "application/json", }, body: JSON.stringify({ "model": "alibaba/qwen3-coder-480b-a35b-instruct", "messages": [ { "role": "user", "content": "Hello!" } ] }), }); console.log(await r.json());
curl -X POST https://api.aimlapi.com/v1/chat/completions \ -H "Authorization: Bearer $AIMLAPI_KEY" \ -H "Content-Type: application/json" \ -d '{"model":"alibaba/qwen3-coder-480b-a35b-instruct","messages":[{"role":"user","content":"Hello!"}]}'
OpenAI-compatible — swap the base URL and it works with your existing SDK.
| Type | Price |
|---|---|
| Input | |
| Output | |
| Benchmark | Score | What it measures | Source | Retrieved |
|---|---|---|---|---|
| SWE-bench Verified | 66.5% | Resolving verified real GitHub issues | Source | July 8, 2026 |
| Intelligence | 11.9 | Composite score across standardised reasoning, knowledge and problem-solving evaluations, measured independently by Artificial Analysis | Source | September 12, 2026 |
| Math | 39.3 | Composite score across standardised mathematics evaluations, measured independently by Artificial Analysis | Source | September 12, 2026 |
| Model | Input | Output | Context | Best for |
|---|---|---|---|---|
Qwen3 Coder This page | Coding + agents | |||
| Reasoning + agents | ||||
| Balanced coding + agents | ||||
| Long-context, multimodal & agentic workflows | ||||
| Reasoning + agents |
Qwen3 Coder has a 262,000 tokens context window and can return up to 65,536 tokens.
Qwen3 Coder takes text as input and returns text.
Use alibaba/qwen3-coder-480b-a35b-instruct as the model id. Requests go to https://api.aimlapi.com/v1/chat/completions.
Qwen3 Coder became available on September 9, 2025.
Qwen3 Coder is priced at input $1.95 / 1M tokens, output $9.75 / 1M tokens.
Yes, Qwen3 Coder can stream responses as they are generated.
Qwen3 Coder was built by Alibaba Cloud.
