Qwen: Qwen3 Coder Next
qwen/qwen3-coder-next
Try Qwen3 Coder Next for free in your browser, and add it to your app for free with Puter.js AI API.
Try it free Add to your app// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms", {
model: "qwen/qwen3-coder-next"
}).then(response => {
document.body.innerHTML = response.message.content;
});
<html>
<body>
<script src="https://js.puter.com/v2/"></script>
<script>
puter.ai.chat("Explain quantum computing in simple terms", {
model: "qwen/qwen3-coder-next"
}).then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
Model Card
Qwen3-Coder-Next is an open-weight coding model from Alibaba's Qwen team with 80B total parameters but only 3B active per token, designed specifically for coding agents and local development with a 256K context window. It uses a sparse Mixture-of-Experts (MoE) architecture with hybrid attention, trained on 800K executable coding tasks using reinforcement learning to excel at long-horizon reasoning, tool calling, and recovering from execution failures. It achieves performance comparable to models with 10-20x more active parameters on benchmarks like SWE-Bench while maintaining low inference costs.
Context Window 262K
tokens
Max Output 236K
tokens
Input Cost $0.12
per million tokens
Output Cost $0.8
per million tokens
Input text
modalities
Tool Use Yes
Release Date Feb 3, 2026
Output Speed 92
tokens / sec
Latency 0.89s
time to first token
Try Qwen3 Coder Next for free
Try Qwen3 Coder Next instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
Benchmarks
How Qwen3 Coder Next performs on standard evaluations.
| Benchmark | Score |
|---|---|
| GPQA Diamond Graduate-level science Q&A | 73.7% |
| Humanity's Last Exam Cross-domain reasoning | 10.1% |
| SciCode Scientific programming | 36.2% |
| IFBench Instruction following | 35.2% |
| LCR Long-context reasoning | 47.0% |
| Terminal-Bench Hard Agentic terminal tasks | 18.2% |
| τ²-Bench Tool use / agents | 79.5% |
Scores sourced from Artificial Analysis.
Find other Qwen models →
Qwen3.8 Max Prime
Qwen3.8 Max Prime is a high-throughput serving tier of Alibaba's Qwen3.8 Max, the Qwen team's 2.4-trillion-parameter Mixture-of-Experts flagship released August 3, 2026. It runs the same underlying weights as standard Qwen3.8 Max, a 1M-token-context model with 95B active parameters and native text, image, and video input, but on faster inference infrastructure. Third-party trackers report roughly 1.5 to 2 times the output throughput of the standard endpoint, at a higher per-token price. Because the weights are unchanged, Prime inherits Qwen3.8 Max's benchmark results, including 67.7 on SWE-bench Pro and a top-three ranking on LMArena Code, putting it behind Claude Fable 5 but ahead of GPT-6 Sol on several agentic coding evaluations. It suits developers running latency-sensitive coding agents or high-concurrency workloads who want Qwen3.8 Max's capability without the standard endpoint's slower response time.
ChatQwen3.8 OmniFlash
Qwen3.8 OmniFlash is Alibaba's first omni-modal model built around agentic capabilities, released September 18, 2026, succeeding Qwen3.5-Omni-Plus. It accepts text, images, audio, and video as input and returns text, pairing native audio-video understanding with reasoning and tool use. It can watch or listen to content, plan a task, call tools, and deliver a finished result, such as an edited video or a meeting summary. Alibaba reports more than a 26% average improvement across 30 evaluations versus Qwen3.5-Omni-Plus, with gains in audio-video agents, coding, long-context tasks, and real-time interaction. It says audio-visual performance approaches Gemini 3.8 Flash, with audio performance exceeding it. With a 1,000,000 token context window, 128,000 token output limit, and pricing of $0.06 per million input tokens and $0.19 per million output tokens, it suits developers building video and audio agents, such as meeting summarization or video-editing pipelines that need tool-calling built in.
ChatQwen3.8 Max (0902)
Qwen3.8 Max (0902) is a September 2026 snapshot of Alibaba's Qwen3.8 Max, a 2.4-trillion-parameter mixture-of-experts flagship with roughly 95 billion active parameters per token. It keeps the 1M-token context window, thinking mode, and tool ecosystem of the base model, with additional post-training on coding and office-work tasks. On Code Arena WebDev it ranks first overall at 1,691 points, ahead of Claude Opus 5 Max (1,687) and Kimi K3 Max (1,674). The largest gains are on TerminalBench 3.0 and ProgramBench Almost Solved, both more than doubling versus the prior snapshot. Reported core scores include GPQA Diamond 92.6 and PaperBench 93.0. Against Claude Opus 5, it leads on several coding benchmarks and on WorkArena, though Opus 5 still leads on most agentic coding rows and both office-work benchmarks. Pricing is unchanged from the base Qwen3.8 Max, making it a straightforward upgrade for coding and office-automation workloads already on the platform.
Frequently Asked Questions
You can access Qwen3 Coder Next by Qwen through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.
Qwen3 Coder Next is free to try with a Puter account. Every account includes a free AI allowance, and you can chat with it in the playground on this page. You can upgrade your account anytime for a larger allowance.
Qwen3 Coder Next is free to integrate using the Puter.js AI API. With the User-Pays Model, you can add AI to your app for $0, since users cover their own AI usage through their Puter account.
| Price per 1M tokens | |
|---|---|
| Input | $0.12 |
| Output | $0.8 |
Qwen3 Coder Next was created by Qwen and released on Feb 3, 2026.
Qwen3 Coder Next supports a context window of 262K tokens. For reference, that is roughly equivalent to 524 pages of text.
Qwen3 Coder Next can generate up to 236K tokens in a single response.
Qwen3 Coder Next accepts the following input types: text. It produces: text.
Yes, Qwen3 Coder Next supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.
Yes — the Qwen3 Coder Next API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.
Add Qwen3 Coder Next to your app for free
Developers can integrate Qwen3 Coder Next for free using the Puter.js AI API.
With the User-Pays Model, each user covers their own AI usage instead of the developer.