MiroMind: MiroThinker 1.7 DeepResearch
miromind/mirothinker-1-7-deepresearch
Access MiroThinker 1.7 DeepResearch from MiroMind 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: "miromind/mirothinker-1-7-deepresearch"
}).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: "miromind/mirothinker-1-7-deepresearch"
}).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="miromind/mirothinker-1-7-deepresearch",
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": "miromind/mirothinker-1-7-deepresearch",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
MiroThinker 1.7 DeepResearch is an open-source deep research agent from MiroMind AI, built on a 235B-parameter Qwen3-235B-A22B-Thinking-2507 mixture-of-experts architecture. It is designed for long-horizon web research, complex multi-step investigation, and prediction tasks rather than general chat.
It scores 74.0 on BrowseComp, 75.3 on BrowseComp-ZH, 82.7 on GAIA-Val-165, and 42.9 on HLE-Text, and MiroMind reports it sets a new state of the art among open-source models on BrowseComp-ZH. The model supports a 256K-token context window and can issue up to 300 tool calls in a single task. MiroMind calls this approach interaction scaling, training the agent to handle deeper and more frequent tool interactions rather than relying only on larger parameter counts or longer context.
Released under Apache 2.0, it's a fit for developers building autonomous research agents, web-browsing pipelines, or report-generation tools that need many sequential tool calls to reach a verified answer.
Context Window 262K
tokens
Max Output 16K
tokens
Input Cost $4
per million tokens
Output Cost $25
per million tokens
Release Date N/A
Model Playground
Try MiroThinker 1.7 DeepResearch instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
More AI Models From MiroMind
Frequently Asked Questions
You can access MiroThinker 1.7 DeepResearch by MiroMind 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 MiroThinker 1.7 DeepResearch 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 | $4 |
| Output | $25 |
MiroThinker 1.7 DeepResearch supports a context window of 262K tokens. For reference, that is roughly equivalent to 524 pages of text.
MiroThinker 1.7 DeepResearch can generate up to 16K tokens in a single response.
Yes — the MiroThinker 1.7 DeepResearch 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 MiroThinker 1.7 DeepResearch to your app without worrying about API keys or setup.
Read the Docs View Tutorials