Qwen: Qwen2.5-VL 7B Instruct
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Qwen 2.5 VL 7B Instruct is a vision-language model capable of understanding images, documents, charts, and videos up to 1 hour. It supports OCR, visual reasoning, and can act as a visual agent for computer/phone use.
Context Window 131K
tokens
Max Output 8K
tokens
Input Cost $0.35
per million tokens
Output Cost $1.05
per million tokens
Input text, image
modalities
Tool Use Yes
Knowledge Cutoff Apr 2024
Release Date Sep 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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ChatQwen3.8 Max
Qwen3.8 Max is Alibaba's flagship large language model, released August 3, 2026 as the most capable model in the Qwen family to date. It uses a mixture-of-experts architecture with 2.4 trillion total parameters and about 95 billion active per request, and accepts text, image, and video input with a context window of up to 1 million tokens. Alibaba positions it for coding and long-horizon agentic work: in testing the model ran autonomously for over 10 days building a self-evolving software harness. Reported benchmarks include 93.0 on PaperBench, 82.8 on IFBench, 86.6 on Terminal-Bench 2.1, and 86.1 on OSWorld-Verified, ahead of Claude Opus 4.8 on several coding and agent tasks and roughly matching Claude Fable 5 and GPT-5.6 Sol, though it trails both on some evaluations. On the Arena.AI leaderboard it ranks as the top Chinese model for text tasks. Alibaba plans to open-source the weights on Hugging Face and ModelScope.
ChatQwen3.7 Flash
Qwen3.7 Flash is the low-cost, fast tier of Alibaba's Qwen3.7 family, released in July 2026. It is a vision-language model that accepts text, image, and video input across a 1 million-token context window, with reasoning enabled by default and a 262K-token thinking budget. Alibaba positions it as an upgrade over Qwen3.6 Flash in multimodal understanding and agent execution, with better object recognition and spatial intelligence. It supports function calling and structured outputs. Pricing is tiered by prompt length. Requests under 32K input tokens cost $0.03/$0.13 per million, rising to $0.20/$0.80 above 256K. Alibaba published no benchmarks at launch. An independent vision evaluation by Roboflow measured strong object identification (84.4%) but weak OCR and object detection, so it fits high-volume multimodal tasks (classification, visual agents, lightweight extraction) better than document-heavy pipelines.
Frequently Asked Questions
You can access Qwen2.5-VL 7B Instruct 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.
Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Qwen2.5-VL 7B Instruct to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.
| Price per 1M tokens | |
|---|---|
| Input | $0.35 |
| Output | $1.05 |
Qwen2.5-VL 7B Instruct was created by Qwen and released on Sep 2024.
Qwen2.5-VL 7B Instruct supports a context window of 131K tokens. For reference, that is roughly equivalent to 262 pages of text.
Qwen2.5-VL 7B Instruct can generate up to 8K tokens in a single response.
Qwen2.5-VL 7B Instruct has a knowledge cutoff date of Apr 2024. This means the model was trained on data available up to that date.
Qwen2.5-VL 7B Instruct accepts the following input types: text, image. It produces: text.
Yes, Qwen2.5-VL 7B 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-VL 7B 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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