MiniMax M1

MiniMax M1

MiniMax
+
+

Related Products

  • Gemini Enterprise Agent Platform
    999 Ratings
    Visit Website
  • LM-Kit.NET
    29 Ratings
    Visit Website
  • Google AI Studio
    30 Ratings
    Visit Website
  • Cloverleaf
    189 Ratings
    Visit Website
  • Unimus
    31 Ratings
    Visit Website
  • Oxylabs
    1,205 Ratings
    Visit Website
  • SafetyCulture
    647 Ratings
    Visit Website
  • TrustInSoft Analyzer
    6 Ratings
    Visit Website
  • AnalyticsCreator
    46 Ratings
    Visit Website
  • Interfacing Integrated Management System (IMS)
    66 Ratings
    Visit Website

About

MiniMax‑M1 is a large‑scale hybrid‑attention reasoning model released by MiniMax AI under the Apache 2.0 license. It supports an unprecedented 1 million‑token context window and up to 80,000-token outputs, enabling extended reasoning across long documents. Trained using large‑scale reinforcement learning with a novel CISPO algorithm, MiniMax‑M1 completed full training on 512 H800 GPUs in about three weeks. It achieves state‑of‑the‑art performance on benchmarks in mathematics, coding, software engineering, tool usage, and long‑context understanding, matching or outperforming leading models. Two model variants are available (40K and 80K thinking budgets), with weights and deployment scripts provided via GitHub and Hugging Face.

About

Muse Spark 1.1 is a multimodal reasoning model from Meta Superintelligence Labs built for agentic tasks, coding, computer use, tool use, and multimodal understanding. The model improves on the original Muse Spark with stronger performance in planning, orchestration, long-context work, coding workflows, and external app interactions. Muse Spark 1.1 can manage a 1 million token context window, remember earlier actions, retrieve important information, compact context, and delegate tasks across parallel subagents. It is designed to operate across tools, MCP servers, custom skills, browsers, native apps, scripts, images, video, PDFs, and audio-based workflows. Developers can access Muse Spark 1.1 through the new Meta Model API public preview, while users can try it in Thinking mode in the Meta AI app and on meta.ai.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

AI researchers, developers, and enterprises needing a solution providing LLM capable of long‑context reasoning, efficient compute, and integration via function calls

Audience

Muse Spark 1.1 is best suited for developers, AI engineers, enterprises, agent builders, coding tool teams, research teams, and productivity-focused users that need a multimodal reasoning model for agentic workflows, coding, computer use, long-context tasks, tool orchestration, and advanced automation

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

$1.25 per 1M tokens (input)
$1.25 per million tokens in input, and $4.25 per million tokens of output
Free Version
Free Trial

Reviews/Ratings

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

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 4.0 / 5
design 5.0 / 5
support 5.0 / 5

Pros & Cons from Real Users

Pros

  • Muse Spark 1.1 has been awesome for the way I actually build with AI: agents, coding workflows, tool calls, debugging loops, and messy real-world tasks that do not fit neatly into a single prompt. It feels much stronger than the first version when I need it to reason through code, work across multiple steps, understand context, and keep an agent moving without constantly falling apart. The multimodal side is also a big plus because being able to work with docs, screenshots, images, and other inputs makes it way more useful for building practical AI products.

Cons

  • It is still early, so I would not call it perfect yet. Like any advanced model, you still need good scaffolding, evals, guardrails, and monitoring if you are putting it into production agent workflows. I also want to see the API ecosystem, docs, examples, and integration patterns mature more, because those things matter a lot when you are building real agentic systems instead of just testing prompts.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

MiniMax
Founded: 2021
Singapore
www.minimax.io/news/minimaxm1

Company Information

Meta
Founded: 2004
United States
meta.ai

Alternatives

MiniMax M3

MiniMax M3

MiniMax

Alternatives

Claude Opus 5

Claude Opus 5

Anthropic
Claude Fable 5

Claude Fable 5

Anthropic
DeepSeek-V3.2

DeepSeek-V3.2

DeepSeek
Claude Mythos 5

Claude Mythos 5

Anthropic
OpenAI o1

OpenAI o1

OpenAI

Categories

Categories

Integrations

Anuma
C
Claude Code
Facebook Messenger
Hermes Agent
Instagram
Java
LangChain
Meta Model API
Muse Image
Objective-C
Odysseus
OpenAI Codex
Ruby
Rust
Scala
SiliconFlow
Solidity
WhatsApp
XML

Integrations

Anuma
C
Claude Code
Facebook Messenger
Hermes Agent
Instagram
Java
LangChain
Meta Model API
Muse Image
Objective-C
Odysseus
OpenAI Codex
Ruby
Rust
Scala
SiliconFlow
Solidity
WhatsApp
XML
Claim MiniMax M1 and update features and information
Claim MiniMax M1 and update features and information
Claim Muse Spark 1.1 and update features and information
Claim Muse Spark 1.1 and update features and information