Qwen: Qwen2.5 7B Instruct Turbo
qwen/qwen2.5-7b-instruct-turbo
Access Qwen2.5 7B Instruct Turbo from Qwen using Puter.js AI API.
Get Started// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms", {
model: "qwen/qwen2.5-7b-instruct-turbo"
}).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/qwen2.5-7b-instruct-turbo"
}).then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
# pip install openai
from openai import OpenAI
client = OpenAI(
base_url="https://api.puter.com/puterai/openai/v1/",
api_key="YOUR_PUTER_AUTH_TOKEN",
)
response = client.chat.completions.create(
model="qwen/qwen2.5-7b-instruct-turbo",
messages=[
{"role": "user", "content": "Explain quantum computing in simple terms"}
],
)
print(response.choices[0].message.content)
curl https://api.puter.com/puterai/openai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_PUTER_AUTH_TOKEN" \
-d '{
"model": "qwen/qwen2.5-7b-instruct-turbo",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
Qwen2.5 7B Instruct Turbo is a 7-billion-parameter instruction-tuned chat model from Alibaba's Qwen team, served as a fast, low-cost Turbo endpoint via Together AI.
It is known for strong coding and math performance relative to its size, scoring 84.8 on HumanEval and 75.5 on MATH, and it excels at instruction following, structured-data understanding, and reliable JSON output. The model supports tool/function calling and handles 29+ languages.
Published comparisons show it outperforming similarly sized open models such as Llama 3.1 8B Instruct and Gemma 2 9B across most tasks.
Choose it when you want a cheap, capable small model for coding assistants, structured extraction, multilingual chat, and high-throughput API workloads.
Context Window 33K
tokens
Max Output 33K
tokens
Input Cost $0.3
per million tokens
Output Cost $0.3
per million tokens
Input text
modalities
Tool Use Yes
Knowledge Cutoff Sep 2024
Release Date Sep 19, 2024
Model Playground
Try Qwen2.5 7B Instruct Turbo instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
More AI Models From Qwen
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ChatQwen3.6 Flash
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ChatQwen3.5 Plus 2026-04-20
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.
Frequently Asked Questions
You can access Qwen2.5 7B Instruct Turbo 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 7B Instruct Turbo 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 | $0.3 |
| Output | $0.3 |
Qwen2.5 7B Instruct Turbo was created by Qwen and released on Sep 19, 2024.
Qwen2.5 7B Instruct Turbo supports a context window of 33K tokens. For reference, that is roughly equivalent to 66 pages of text.
Qwen2.5 7B Instruct Turbo can generate up to 33K tokens in a single response.
Qwen2.5 7B Instruct Turbo has a knowledge cutoff date of Sep 2024. This means the model was trained on data available up to that date.
Qwen2.5 7B Instruct Turbo accepts the following input types: text. It produces: text.
Yes, Qwen2.5 7B Instruct Turbo 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 7B Instruct Turbo 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.
Get started with Puter.js
Add Qwen2.5 7B Instruct Turbo to your app without worrying about API keys or setup.
Read the Docs View Tutorials