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>
More AI Models From Qwen
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.
ChatQwen3.6 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.
ChatQwen3.6 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
Qwen2.5 32B Instruct is no longer available through Puter.js. Explore other AI models for alternatives.
| Price per 1M tokens | |
|---|---|
| Input | $0.7 |
| Output | $2.8 |
Qwen2.5 32B Instruct was created by Qwen and released on Sep 19, 2024.
Qwen2.5 32B Instruct supports a context window of 131K tokens. For reference, that is roughly equivalent to 262 pages of text.
Qwen2.5 32B Instruct can generate up to 8K tokens in a single response.
Qwen2.5 32B Instruct accepts the following input types: text. It produces: text.
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.
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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