Qwen: Qwen2.5 32B Instruct

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Qwen2.5 32B Instruct is a 32-billion-parameter instruction-tuned chat model from Alibaba's Qwen team, released in September 2024 as part of the Qwen2.5 family, which was pretrained on 18 trillion tokens.

On instruct-model benchmarks it scores 83.1 on MATH, 88.4 on HumanEval, 84.0 on MBPP, 69.0 on MMLU-Pro, and 74.5 on Arena-Hard. In Qwen's published comparison it leads GPT-4o mini and Gemma2 27B IT on most of these tasks, with math and coding as its strongest areas.

The model supports function calling, structured JSON output, more than 29 languages, a 131,072-token context window, and up to 8,192 output tokens. It fits developers who want stronger reasoning, math, and coding than the 14B variant without paying for the 72B flagship.

Context Window 131K

tokens

Max Output 8K

tokens

Input Cost $0.7

per million tokens

Output Cost $2.8

per million tokens

Input text

modalities

Tool Use Yes

Release Date Sep 19, 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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Qwen3.5 Plus is a proprietary hosted model from Alibaba, built on the Qwen3.5-397B-A17B Mixture-of-Experts architecture with 397 billion total parameters and 17 billion active per token. Its headline feature is a 1-million-token native context window — among the largest available via API — making it well suited for processing entire codebases, long documents, or extended multi-turn conversations in a single request. It supports both a deep-thinking mode and an "Auto" mode that adaptively invokes tools like web search and code interpreters. This April 20, 2026 snapshot reflects ongoing improvements to the model since its original February 2026 launch. The Qwen3.5 series demonstrated strong multimodal performance across reasoning, coding, and vision tasks. A solid general-purpose option for developers needing large-context capabilities without migrating to the newer Qwen3.6 line.

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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.

Frequently Asked Questions

How do I use Qwen2.5 32B Instruct?

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

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

Qwen2.5 32B Instruct costs $0.7 per 1M input tokens and $2.8 per 1M output tokens.

	Price per 1M tokens
Input	$0.7
Output	$2.8

Who created Qwen2.5 32B Instruct?

Qwen2.5 32B Instruct was created by Qwen and released on Sep 19, 2024.

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

Qwen2.5 32B Instruct supports a context window of 131K tokens. For reference, that is roughly equivalent to 262 pages of text.

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

Qwen2.5 32B Instruct can generate up to 8K tokens in a single response.

What types of input can Qwen2.5 32B Instruct process?

Qwen2.5 32B Instruct accepts the following input types: text. It produces: text.

Does Qwen2.5 32B Instruct support tool use (function calling)?

Yes, Qwen2.5 32B Instruct supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.

How does Qwen2.5 32B Instruct perform on benchmarks?

Qwen2.5 32B Instruct scores 6.9 on the Artificial Analysis Intelligence Index, outperforming 23% of tracked models.

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

Yes — the Qwen2.5 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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