Qwen: Qwen2.5 Coder 32B Instruct

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Qwen2.5 Coder 32B Instruct is the largest model in Alibaba's Qwen2.5-Coder family, a code-specialized model released in November 2024 and trained for code generation, code repair, and code reasoning.

On code generation it scores 92.7 on HumanEval and 86.3 on EvalPlus, and the Qwen team reports overall coding performance competitive with GPT-4o. On Aider's code repair benchmark it scores 73.7, comparable to GPT-4o, and it scores 75.2 on MdEval, a multi-language code repair benchmark, first among open models at release. It covers more than 40 programming languages, scoring 65.9 on McEval, with notably strong results in less common languages like Haskell and Racket.

This route offers a 32K context window at low per-token cost. It fits developers who want code completion, bug fixing, and code explanation without paying frontier-model prices.

Context Window 33K

tokens

Max Output 120K

tokens

Input Cost $0.03

per million tokens

Output Cost $0.11

per million tokens

Release Date Nov 11, 2024

Code Example

Add AI to your app with the Puter.js AI API, no API keys or setup required.

// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';

puter.ai.chat("Explain quantum computing in simple terms").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").then(response => {
            document.body.innerHTML = response.message.content;
        });
    </script>
</body>
</html>

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Qwen3.6 27B

Qwen3.6 27B is a dense 27-billion-parameter multimodal model from Alibaba's Qwen team, purpose-built for agentic coding and repository-level reasoning. It scores 77.2% on SWE-bench Verified and 59.3% on Terminal-Bench 2.0, outperforming the previous-generation Qwen3.5-397B-A17B across all major coding benchmarks despite being far smaller. It natively supports text, image, and video inputs with a 262K-token context window, extendable to 1M tokens. A standout feature is Thinking Preservation, which retains reasoning traces across conversation turns — reducing redundant computation in multi-step agent loops. The model uses a hybrid attention architecture combining Gated DeltaNet with traditional self-attention. Ideal for developers building coding agents, multi-turn tool-use workflows, or frontend generation pipelines.

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Qwen3.6 Max Preview

Qwen3.6 Max Preview is Alibaba's most capable language model to date — a proprietary flagship that claimed the top score on six major coding benchmarks at its April 20, 2026 release. It leads on SWE-bench Pro, Terminal-Bench 2.0, SkillsBench, QwenClawBench, QwenWebBench, and SciCode. The Artificial Analysis Intelligence Index rates it at 52, well above the median for reasoning models in its price tier. It supports a 256K-token context window and is text-only at launch. As a preview release, Alibaba is still actively iterating on the model. Best suited for teams building coding agents, scientific computing tools, or frontend generation systems that need peak benchmark performance.

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Qwen3.6 35B A3B

Qwen3.6 35B A3B is a sparse Mixture-of-Experts model with 35 billion total parameters but only 3 billion active per token, making it highly efficient for inference. Developed by Alibaba's Qwen team, it scores 73.4% on SWE-bench Verified and 51.5% on Terminal-Bench 2.0 — significantly outperforming dense models like Gemma 4-31B (52.0% on SWE-bench Verified). It natively handles text, image, and video with a 262K-token context window, extendable to 1M tokens. The model supports Thinking Preservation for stable multi-turn reasoning and includes native tool-calling capabilities. Released under Apache 2.0, it was the first open-weight model in the Qwen3.6 family. A strong choice for developers who want frontier-adjacent coding performance at a fraction of the compute cost of larger models.

Frequently Asked Questions

How do I use Qwen2.5 Coder 32B Instruct?

Qwen2.5 Coder 32B Instruct is no longer available through Puter.js. Explore other AI models for alternatives.

What is the pricing for Qwen2.5 Coder 32B Instruct?

Qwen2.5 Coder 32B Instruct costs $0.03 per 1M input tokens and $0.11 per 1M output tokens.

	Price per 1M tokens
Input	$0.03
Output	$0.11

Who created Qwen2.5 Coder 32B Instruct?

Qwen2.5 Coder 32B Instruct was created by Qwen and released on Nov 11, 2024.

What is the context window of Qwen2.5 Coder 32B Instruct?

Qwen2.5 Coder 32B Instruct supports a context window of 33K tokens. For reference, that is roughly equivalent to 66 pages of text.

What is the max output length of Qwen2.5 Coder 32B Instruct?

Qwen2.5 Coder 32B Instruct can generate up to 120K tokens in a single response.

Does it work with React / Vue / Vanilla JS / Node / etc.?

Yes — the Qwen2.5 Coder 32B Instruct 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.

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