MiniMax M3

MiniMax M3

MiniMax
SubQ Snap 1.1

SubQ Snap 1.1

Subquadratic
+
+

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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.

About

SubQ Snap is a hosted multimodal decision model for developers building AI agents and enterprise workflows. Through Subquadratic’s API, applications send text or image context with defined questions and receive structured answers such as labels, choices, scores, and probabilities. This supports tasks including tool and file selection, routing, triage, guardrails, ranking, classification, and checking whether a test or result meets specified criteria. The model accepts up to 384K tokens of context and supports image input. It is designed for bounded decisions rather than open-ended text generation, so it can be used alongside a language model that handles planning or writing. Public-preview API documentation includes request examples, model access details, and decision formats.

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

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

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

Audience

Developers and enterprise teams building AI agents and workflows that need structured decisions from text or image context.

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 Not Supported

API

Offers API Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

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

Pricing

$0.05/1M input tokens
$0.05 per 1 million input tokens; output tokens are free. SubQ Snap is in public preview, with access subject to capacity limits.
Free Version Not Supported
Free Trial Not Supported

Reviews/Ratings

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

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:

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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

MiniMax
Founded: 2021
Singapore
www.minimax.io

Company Information

Subquadratic
Founded: 2025
United States
subq.ai/

Alternatives

Alternatives

GPT-5.6 Sol

GPT-5.6 Sol

OpenAI
GPT-6 Astra

GPT-6 Astra

OpenAI
Claude Opus 5

Claude Opus 5

Anthropic
MiniMax

MiniMax

MiniMax AI
SubQ Snap

SubQ Snap

Subquadratic

Categories

Categories

AI Decision Models Supported

Integrations

APIFree Supported
Alibaba AI Coding Plan Supported
BLACKBOX AI Supported
Claude Code Supported
Clawd.run Supported
Cline Supported
ClinePass Supported
Fireworks AI Supported
Kilo Code Supported
MaxHermes Supported
MiniMax Agent Supported
MiniMax Code Supported
Ollama Supported
OpenAI Not Supported
OpenClaw Supported
OpenCode Zen Supported
OpenTag Supported
Pi Agent Supported
Roo Code Supported
Together AI Supported

Integrations

APIFree Not Supported
Alibaba AI Coding Plan Not Supported
BLACKBOX AI Not Supported
Claude Code Not Supported
Clawd.run Not Supported
Cline Not Supported
ClinePass Not Supported
Fireworks AI Not Supported
Kilo Code Not Supported
MaxHermes Not Supported
MiniMax Agent Not Supported
MiniMax Code Not Supported
Ollama Not Supported
OpenAI Supported
OpenClaw Not Supported
OpenCode Zen Not Supported
OpenTag Not Supported
Pi Agent Not Supported
Roo Code Not Supported
Together AI Not Supported
Claim MiniMax M3 and update features and information
Claim MiniMax M3 and update features and information
Claim SubQ Snap 1.1 and update features and information
Claim SubQ Snap 1.1 and update features and information