MiniMax: MiniMax M2.5
minimax/minimax-m2.5
Access MiniMax M2.5 from MiniMax 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: "minimax/minimax-m2.5"
}).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: "minimax/minimax-m2.5"
}).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="minimax/minimax-m2.5",
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": "minimax/minimax-m2.5",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
MiniMax M2.5 is a 230B-parameter Mixture-of-Experts model (10B active) from Shanghai-based MiniMax, designed for real-world productivity with state-of-the-art performance in coding (80.2% SWE-Bench Verified), agentic tool use, and search tasks. It rivals top models from Anthropic and OpenAI while costing 1/10th to 1/20th the price, positioning itself as frontier intelligence 'too cheap to meter.' The model excels at full-stack development, office work (Word, Excel, PowerPoint), and autonomous agent workflows.
Context Window 205K
tokens
Max Output 197K
tokens
Input Cost $0.3
per million tokens
Output Cost $1.2
per million tokens
Input text
modalities
Tool Use Yes
Release Date Feb 12, 2026
Output Speed 76
tokens / sec
Latency 1.38s
time to first token
Model Playground
Try MiniMax M2.5 instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
Benchmarks
How MiniMax M2.5 performs on standard evaluations.
| Benchmark | Score |
|---|---|
| GPQA Diamond Graduate-level science Q&A | 84.8% |
| Humanity's Last Exam Cross-domain reasoning | 19.1% |
| SciCode Scientific programming | 42.6% |
| IFBench Instruction following | 71.6% |
| LCR Long-context reasoning | 66.0% |
| Terminal-Bench Hard Agentic terminal tasks | 34.8% |
| τ²-Bench Tool use / agents | 95.3% |
Scores sourced from Artificial Analysis.
Find other MiniMax models →
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ChatMiniMax M2.7
MiniMax M2.7 is a proprietary reasoning LLM from Chinese AI startup MiniMax, released on March 18, 2026, notable for being one of the first commercial models to actively participate in its own training through autonomous self-evolution loops. It excels at agentic coding workflows with a 56.2% score on SWE-Pro and strong performance in office productivity tasks, scoring the highest ELO (1495) on GDPval-AA among open-source-tier models. It targets developers building complex agent systems and automated workflows.
ChatMiniMax M2.7 Highspeed
MiniMax M2.7 Highspeed is a high-throughput, inference-optimized variant of MiniMax M2.7, delivering approximately 100 tokens per second — roughly 66% faster than the standard version. It shares the same model weights and MoE architecture as M2.7, so output quality and reasoning capability are identical; the speed advantage comes entirely from inference-layer routing and batching optimizations. It supports text and image inputs with a 204K context window and features automatic prompt caching and parallel tool calling. Best suited for live coding assistants, autonomous agent pipelines, and interactive workflows where low latency and high throughput matter.
Frequently Asked Questions
You can access MiniMax M2.5 by MiniMax 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 MiniMax M2.5 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 | $1.2 |
MiniMax M2.5 was created by MiniMax and released on Feb 12, 2026.
MiniMax M2.5 supports a context window of 205K tokens. For reference, that is roughly equivalent to 410 pages of text.
MiniMax M2.5 can generate up to 197K tokens in a single response.
MiniMax M2.5 accepts the following input types: text. It produces: text.
Yes, MiniMax M2.5 supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.
MiniMax M2.5 scores 33.7 on the Artificial Analysis Intelligence Index, outperforming 82% of tracked models.
Yes — the MiniMax M2.5 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 MiniMax M2.5 to your app without worrying about API keys or setup.
Read the Docs View Tutorials