MiroMind: MiroThinker 1.7 DeepResearch Mini
miromind/mirothinker-1-7-deepresearch-mini
Access MiroThinker 1.7 DeepResearch Mini 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-mini"
}).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-mini"
}).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-mini",
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-mini",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
MiroThinker 1.7 DeepResearch Mini is an open-source deep research agent from MiroMind AI, a 30B-parameter mixture-of-experts model built on the Qwen3-30B-A3B-Thinking-2507 architecture. It is the smaller sibling of MiroThinker 1.7 DeepResearch, aimed at the same long-horizon web research and multi-step investigation tasks at lower compute cost.
It scores 72.3 on BrowseComp-ZH, which MiroMind reports as a new state of the art among open-source models at this parameter scale. Like the full-size model, it supports a 256K-token context window and can issue up to 300 tool calls per task, using the same interaction-scaling training approach that emphasizes deeper and more frequent tool use over simply adding parameters.
Released under Apache 2.0, it suits developers who want MiroThinker's research-agent behavior in a lower-cost, faster model for high-volume or latency-sensitive deep-research API calls.
Context Window 262K
tokens
Max Output 16K
tokens
Input Cost $1.25
per million tokens
Output Cost $10
per million tokens
Release Date N/A
Model Playground
Try MiroThinker 1.7 DeepResearch Mini 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 Mini 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 Mini 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 | $1.25 |
| Output | $10 |
MiroThinker 1.7 DeepResearch Mini supports a context window of 262K tokens. For reference, that is roughly equivalent to 524 pages of text.
MiroThinker 1.7 DeepResearch Mini can generate up to 16K tokens in a single response.
Yes — the MiroThinker 1.7 DeepResearch Mini 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 Mini to your app without worrying about API keys or setup.
Read the Docs View Tutorials