MiniMax M3

MiniMax M3

MiniMax
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About

Meta Model API is a new developer API for building with Muse Spark 1.1, Meta’s multimodal reasoning model built for agentic tasks, coding, tool use, computer use, and multimodal understanding. Now in public preview, it gives developers a way to access Muse Spark 1.1 through an OpenAI-compatible package, making it easier to point existing clients at the API, keep the same code structure, and set the model to muse-spark-1.1. Muse Spark 1.1 is designed for personal agentic tasks that require planning and orchestration across external apps and services, with the ability to generalize to new native tools, MCP servers, and custom skills. As a main agent, it can gather context, make a plan, and delegate execution across parallel subagents; as a subagent, it follows its role, understands available tools, and knows when to escalate back. The model can actively manage a 1 million-token context window, remember actions, retrieve information from much earlier work, and compact context.

About

MiniMax M3 is an open-weight multimodal AI model designed for coding, agentic workflows, long-context reasoning, and complex automation tasks. The model combines frontier-level coding performance, native multimodal understanding, and a context window of up to 1 million tokens. MiniMax M3 uses MiniMax Sparse Attention to improve long-context efficiency while reducing compute requirements for large-scale inputs. It supports text, image, and video understanding, making it useful for workflows that combine code, documents, visual references, and tool-driven tasks. The model is built for repository-scale reasoning, software engineering, autonomous task execution, tool calling, and multi-step agent workflows. MiniMax M3 helps developers, AI teams, and enterprises build capable agents that can reason across large contexts and work with multimodal information.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Developers and anyone needing a multimodal model API for coding agents, tool-using workflows, computer use, and long-context automation

Audience

MiniMax M3 is best suited for developers, AI engineers, coding assistant builders, enterprise automation teams, research teams, data teams, agent developers, and organizations that need open-weight AI for coding, long-context reasoning, multimodal understanding, tool use, repository analysis, and autonomous workflows

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

$1.25 per 1M tokens
Free Version Not Supported
Free Trial Not Supported

Pricing

$0.30 per million input tokens
$0.30 per million input tokens and $1.20 per million output tokens
Free Version Supported
Free Trial Not Supported

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 5.0 / 5
ease 4.0 / 5
features 4.0 / 5

Pros & Cons from Real Users

Pros

  • The multimodal side also makes it more flexible than a code-only model. Being able to work across text, images, video-style understanding, and code gives it more room to support real workflows instead of being boxed into one narrow use case. For agent builders, the best part is that M3 is clearly designed around tool use and multi-step execution. MiniMax specifically calls out autonomous task decomposition and tool invocation, which is exactly what matters when a model is powering coding assistants, workflow agents, or automated dev tools.

Cons

  • The main catch is infrastructure and trust. Even with sparse attention and MoE efficiency, this is still a large model, so deployment is not casual. I would also want to benchmark it on my own repos before depending on it for production work.

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

Meta
United States
developer.meta.com/ai/products/meta-model-api/

Company Information

MiniMax
Founded: 2021
Singapore
www.minimax.io

Alternatives

Alternatives

MiniMax

MiniMax

MiniMax AI
MiniMax M1

MiniMax M1

MiniMax

Categories

Categories

AI Coding Models Supported
AI Models Supported
Foundation Models Supported
Multimodal Models Supported

Integrations

Claude Code Supported
Hermes Agent Supported
OpenClaw Supported
APIFree Not Supported
Alibaba AI Coding Plan Not Supported
BLACKBOX AI Not Supported
Clawd.run Not Supported
Continue Supported
Factory Droid Not Supported
GitHub Supported
Llama 4 Behemoth Supported
Llama 4 Scout Supported
LlamaIndex Supported
MiniMax Agent Not Supported
MiniMax Mavis Not Supported
Muse Spark 1.1 Supported
Muse Spark 1.2 Supported
OpenAI Supported
OpenCode Zen Not Supported
Vision Agents Not Supported

Integrations

Claude Code Supported
Hermes Agent Supported
OpenClaw Supported
APIFree Supported
Alibaba AI Coding Plan Supported
BLACKBOX AI Supported
Clawd.run Supported
Continue Not Supported
Factory Droid Supported
GitHub Not Supported
Llama 4 Behemoth Not Supported
Llama 4 Scout Not Supported
LlamaIndex Not Supported
MiniMax Agent Supported
MiniMax Mavis Supported
Muse Spark 1.1 Not Supported
Muse Spark 1.2 Not Supported
OpenAI Not Supported
OpenCode Zen Supported
Vision Agents Supported
Claim Meta Model API and update features and information
Claim Meta Model API and update features and information
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