MiniMax: MiniMax M3
Try MiniMax M3 for free in your browser, and add it to your app for free with Puter.js AI API.
Try it free Add to your app// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms", {
model: "minimax/minimax-m3"
}).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-m3"
}).then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
Model Card
MiniMax M3 is a frontier-level multimodal language model built for long-horizon coding, agentic workflows, and complex reasoning. It introduces MiniMax Sparse Attention (MSA), which delivers 15x faster decoding and 9x faster prefill at 1M-token context compared to the prior generation.
M3 scores 59.0% on SWE-Bench Pro — surpassing GPT-5.5 and Gemini 3.1 Pro — and achieves the highest score on Claw-Eval (74.5%) for autonomous agent tasks. It accepts text, image, and video inputs natively and supports tool calling through standard MCP scaffolding.
Ideal for developers building coding agents, long-document pipelines, and multi-step automation that require sustained, multi-hour autonomous execution.
Context Window 1M
tokens
Max Output 512K
tokens
Input Cost $0.3
per million tokens
Output Cost $1.2
per million tokens
Input text, image, video
modalities
Tool Use Yes
Release Date May 31, 2026
Output Speed 97
tokens / sec
Latency 0.85s
time to first token
Try MiniMax M3 for free
Try MiniMax M3 instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
Benchmarks
How MiniMax M3 performs on standard evaluations.
| Benchmark | Score |
|---|---|
| GPQA Diamond Graduate-level science Q&A | 92.9% |
| Humanity's Last Exam Cross-domain reasoning | 39.0% |
| SciCode Scientific programming | 47.1% |
| IFBench Instruction following | 82.9% |
| LCR Long-context reasoning | 83.0% |
| Terminal-Bench Hard Agentic terminal tasks | 42.4% |
| τ²-Bench Tool use / agents | 88.9% |
Scores sourced from Artificial Analysis.
Find other MiniMax models →
MiniMax 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.
ChatMiniMax M2.5
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.
Frequently Asked Questions
You can access MiniMax M3 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.
MiniMax M3 is free to try with a Puter account. Every account includes a free AI allowance, and you can chat with it in the playground on this page. You can upgrade your account anytime for a larger allowance.
MiniMax M3 is free to integrate using the Puter.js AI API. With the User-Pays Model, you can add AI to your app for $0, since users cover their own AI usage through their Puter account.
| Price per 1M tokens | |
|---|---|
| Input | $0.3 |
| Output | $1.2 |
MiniMax M3 was created by MiniMax and released on May 31, 2026.
MiniMax M3 supports a context window of 1M tokens. For reference, that is roughly equivalent to 2,097 pages of text.
MiniMax M3 can generate up to 512K tokens in a single response.
MiniMax M3 accepts the following input types: text, image, video. It produces: text.
Yes, MiniMax M3 supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.
MiniMax M3 scores 29.2 on the Artificial Analysis Intelligence Index, outperforming 81% of tracked models. On coding, it scores 58.6 (outperforms 66% of models).
Yes — the MiniMax M3 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.
Add MiniMax M3 to your app for free
Developers can integrate MiniMax M3 for free using the Puter.js AI API.
With the User-Pays Model, each user covers their own AI usage instead of the developer.