Qwen: Qwen2.5 14B Instruct 1M
qwen/qwen2.5-14b-instruct-1m
Access Qwen2.5 14B Instruct 1M 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/qwen2.5-14b-instruct-1m"
}).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/qwen2.5-14b-instruct-1m"
}).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/qwen2.5-14b-instruct-1m",
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/qwen2.5-14b-instruct-1m",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
Qwen2.5 14B Instruct 1M is the long-context version of Alibaba's Qwen2.5 14B Instruct, released in January 2025 as part of the Qwen2.5-1M series. It is a 14.7-billion-parameter instruction-tuned text model built to handle inputs of up to roughly 1 million tokens.
The extended context comes from long-context training plus length extrapolation with Dual Chunk Attention. On the 1M-token passkey retrieval test the 14B model finds the hidden information with near-perfect accuracy, and on long-context benchmarks such as RULER it scores above 90, beating Qwen2.5-Turbo and GPT-4o-mini across multiple datasets. Short-text performance stays comparable to the standard 128K version.
It fits developers who need to process entire codebases, large document collections, or long transcripts in a single request. Output is capped at 8K tokens per response.
Context Window 1M
tokens
Max Output 8K
tokens
Input Cost $0.81
per million tokens
Output Cost $3.22
per million tokens
Input text
modalities
Release Date Jan 26, 2025
Model Playground
Try Qwen2.5 14B Instruct 1M instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
More AI Models From Qwen
Qwen3.7 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.
ChatQwen3.7 Plus
Qwen3.7 Plus is Alibaba's multimodal agent model, released in June 2026, combining vision-language understanding with full agentic capabilities across a 1 million-token context window. Unlike the text-only Qwen3.7 Max, Plus ingests images and video alongside text, processed through early-fusion training so vision and language are jointly understood from the first layer. This enables GUI grounding — the model can interpret screenshots and issue precise on-screen actions — scoring 79.0 on ScreenSpot Pro, placing it alongside Claude Computer Use and OpenAI Operator in the GUI automation tier. Beyond vision, it adds deep reasoning, self-programming, tool invocation, and autonomous iteration: the model writes and tests code, calls external APIs, and loops until the task is done. On the Artificial Analysis Intelligence Index it scores 53. Choose it over Qwen3.7 Max when your workflow requires image or video inputs, browser/desktop automation, or end-to-end agentic pipelines that combine seeing, reasoning, and doing.
ChatQwen3.7 Max
Qwen3.7 Max is Alibaba's flagship proprietary reasoning model, released in May 2026, built for long-horizon agentic workloads with a 1 million-token context window and a chain-of-thought reasoning architecture. It is purpose-built for complex, multi-step autonomous tasks. Alibaba demonstrated the model running for 35 hours without degradation, executing over 1,000 tool calls in a single session — making it a strong candidate for coding agents, automated pipelines, and deep document analysis. On benchmarks, it ranks 13th globally on LM Arena's text leaderboard and scores 56.6 on the Artificial Analysis Intelligence Index, making it the highest-ranked Chinese model on that index. It posted 90.2 on Arena-Hard v2 and 72.5 on SWE-Bench Verified. Qwen3.7 Max supports the Anthropic API protocol natively, so it integrates cleanly with tooling like Claude Code. It is well-suited for developers building coding assistants, research agents, or any API use case requiring extended reasoning over large contexts.
Frequently Asked Questions
You can access Qwen2.5 14B Instruct 1M 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 14B Instruct 1M 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 | $0.81 |
| Output | $3.22 |
Qwen2.5 14B Instruct 1M was created by Qwen and released on Jan 26, 2025.
Qwen2.5 14B Instruct 1M supports a context window of 1M tokens. For reference, that is roughly equivalent to 2,016 pages of text.
Qwen2.5 14B Instruct 1M can generate up to 8K tokens in a single response.
Qwen2.5 14B Instruct 1M accepts the following input types: text. It produces: text.
Yes — the Qwen2.5 14B Instruct 1M 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 14B Instruct 1M to your app without worrying about API keys or setup.
Read the Docs View Tutorials