MiniMax M3

MiniMax M3

MiniMax
5.0 out of 5 stars
LongLLaMA MiniMax M3

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LongLLaMA:

About

This repository contains the research preview of LongLLaMA, a large language model capable of handling long contexts of 256k tokens or even more. LongLLaMA is built upon the foundation of OpenLLaMA and fine-tuned using the Focused Transformer (FoT) method. LongLLaMA code is built upon the foundation of Code Llama. We release a smaller 3B base variant (not instruction tuned) of the LongLLaMA model on a permissive license (Apache 2.0) and inference code supporting longer contexts on hugging face. Our model weights can serve as the drop-in replacement of LLaMA in existing implementations (for short context up to 2048 tokens). Additionally, we provide evaluation results and comparisons against the original OpenLLaMA models.
MiniMax M3:

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.
LongLLaMA:

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported
MiniMax M3:

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
LongLLaMA:

Audience

Users interested in a powerful Large Language Model solution
MiniMax M3:

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
LongLLaMA:

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported
MiniMax M3:

Support

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

API

Offers API Not Supported
MiniMax M3:

API

Offers API Supported
LongLLaMA:

Screenshots and Videos

MiniMax M3:

Screenshots and Videos

LongLLaMA:

Pricing

Free
Free Version Supported
Free Trial Not Supported
MiniMax M3:

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
LongLLaMA:

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
MiniMax M3:

Reviews/Ratings

Overall 5.0 / 5
ease 4.0 / 5
features 4.0 / 5
MiniMax M3:

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.
LongLLaMA:

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported
MiniMax M3:

Training

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

Company Information

LongLLaMA
github.com/CStanKonrad/long_llama
MiniMax M3:

Company Information

MiniMax
Founded: 2021
Singapore
www.minimax.io
LongLLaMA:

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LongLLaMA:
Inkling

Inkling

Thinking Machines Lab
MiniMax M3:
MiniMax

MiniMax

MiniMax AI
LongLLaMA:

Categories

AI Coding Models Supported
AI Models Supported
MiniMax M3:

Categories

LongLLaMA:

Integrations

Alibaba AI Coding Plan Not Supported
BLACKBOX AI Not Supported
Clawd.run Not Supported
Cline Not Supported
ClinePass Not Supported
Factory Droid Not Supported
Hermes Agent Not Supported
Kilo Code Not Supported
MaxHermes Not Supported
MiniMax Agent Not Supported
MiniMax Code Not Supported
MiniMax Mavis Not Supported
Ollama Not Supported
OpenClaw Not Supported
OpenCode Go Not Supported
OpenCode Zen Not Supported
Pi Agent Not Supported
Roo Code Not Supported
Tabbit Browser Not Supported
Together AI Not Supported
MiniMax M3:

Integrations

Alibaba AI Coding Plan Supported
BLACKBOX AI Supported
Clawd.run Supported
Cline Supported
ClinePass Supported
Factory Droid Supported
Hermes Agent Supported
Kilo Code Supported
MaxHermes Supported
MiniMax Agent Supported
MiniMax Code Supported
MiniMax Mavis Supported
Ollama Supported
OpenClaw Supported
OpenCode Go Supported
OpenCode Zen Supported
Pi Agent Supported
Roo Code Supported
Tabbit Browser Supported
Together AI Supported
LongLLaMA:
Claim LongLLaMA and update features and information
Claim LongLLaMA and update features and information
MiniMax M3:
Claim MiniMax M3 and update features and information
Claim MiniMax M3 and update features and information