Xiaomi: MiMo-V2-Flash
xiaomi/mimo-v2-flash
Access MiMo-V2-Flash from Xiaomi 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: "xiaomi/mimo-v2-flash"
}).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: "xiaomi/mimo-v2-flash"
}).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="xiaomi/mimo-v2-flash",
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": "xiaomi/mimo-v2-flash",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
MiMo-V2-Flash is Xiaomi's open-source Mixture-of-Experts language model with 309B total parameters (15B active), designed for high-speed reasoning, coding, and agentic workflows. It uses a hybrid attention architecture with Multi-Token Prediction to achieve up to 150 tokens/second inference while keeping costs extremely low. The model excels at software engineering benchmarks and supports a 256K context window.
Context Window 262K
tokens
Max Output 66K
tokens
Input Cost $0.1
per million tokens
Output Cost $0.3
per million tokens
Release Date Dec 14, 2025
Output Speed 118
tokens / sec
Latency 1.24s
time to first token
Model Playground
Try MiMo-V2-Flash instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
Benchmarks
How MiMo-V2-Flash performs on standard evaluations.
| Benchmark | Score |
|---|---|
| GPQA Diamond Graduate-level science Q&A | 65.6% |
| Humanity's Last Exam Cross-domain reasoning | 8.0% |
| LiveCodeBench Recent coding problems | 40.2% |
| SciCode Scientific programming | 25.9% |
| AIME 2025 Advanced math exam | 67.7% |
| IFBench Instruction following | 39.9% |
| LCR Long-context reasoning | 31.3% |
| Terminal-Bench Hard Agentic terminal tasks | 25.8% |
| τ²-Bench Tool use / agents | 83.9% |
Scores sourced from Artificial Analysis.
Find other Xiaomi models →
MiMo-V2.5
MiMo V2.5 is a native omnimodal model from Xiaomi that processes text, images, video, and audio within a single architecture and a 1M-token context window. It delivers agentic performance close to its larger sibling, MiMo V2.5 Pro, at roughly half the token cost — scoring 62.3 on ClawEval (general) and 23.8 on ClawEval Multimodal. On video understanding, it reaches 87.7 on Video-MME, competitive with Gemini 3 Pro. Image understanding benchmarks include 81.0 on CharXiv RQ and 77.9 on MMMU-Pro. Priced at $0.40 per million input tokens and $2.00 per million output tokens, MiMo V2.5 is a strong fit for production agent pipelines where you need multimodal perception and reasoning without flagship-tier cost.
ChatMiMo-V2.5-Pro
MiMo V2.5 Pro is Xiaomi's most capable model, built for complex software engineering, long-horizon agentic tasks, and autonomous multi-step workflows spanning over a thousand tool calls. It scores 57.2 on SWE-bench Pro, 63.8 on ClawEval, and 72.9 on τ3-Bench — placing it alongside Claude Opus 4.6 and GPT-5.4 across most agentic evaluations. Notably, it achieves this while using roughly 40–60% fewer tokens per trajectory than comparable frontier models. The 1M-token context window and 131K max output support entire codebases and extended autonomous sessions. Priced at $1.00 per million input tokens and $3.00 per million output tokens, MiMo V2.5 Pro targets developers building autonomous agents, code-generation pipelines, and complex tool-use workflows where sustained coherence over long contexts is critical.
Frequently Asked Questions
You can access MiMo-V2-Flash by Xiaomi 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 MiMo-V2-Flash 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 | $0.1 |
| Output | $0.3 |
MiMo-V2-Flash was created by Xiaomi and released on Dec 14, 2025.
MiMo-V2-Flash supports a context window of 262K tokens. For reference, that is roughly equivalent to 524 pages of text.
MiMo-V2-Flash can generate up to 66K tokens in a single response.
MiMo-V2-Flash scores 30.3 on the Artificial Analysis Intelligence Index, outperforming 69% of tracked models. On coding, it scores 25.8 (outperforms 62% of models). On math, it scores 67.7 (outperforms 62% of models).
Yes — the MiMo-V2-Flash 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 MiMo-V2-Flash to your app without worrying about API keys or setup.
Read the Docs View Tutorials