GPT-6 Sol

GPT-6 Sol

OpenAI
MiniMax M3

MiniMax M3

MiniMax
+
+

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About

GPT-6 Sol is an OpenAI model designed to bring GPT-6-class intelligence to professional work, coding, computer use, and agentic workflows at a lower cost than GPT-6 Astra. The model improves on GPT-5.6 Sol in factual reliability, software engineering, business automation, and long-horizon computer tasks. Developers can adjust reasoning effort depending on task complexity, allowing Sol to allocate more computation to difficult problems while using less for simpler work. GPT-6 Sol also introduces a clearer collaboration style with less jargon, fewer unnecessary details, and more concise technical communication. Improved prompt caching helps agents reuse long contexts more efficiently while reducing latency and cached-input costs. GPT-6 Sol is available through ChatGPT Work, Codex, and the OpenAI API as gpt-6-sol.

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
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Software developers, AI engineers, agent builders, analysts, knowledge workers, enterprises, and application developers that need advanced reasoning, coding, computer use, and professional workflow capabilities at a lower cost than OpenAI’s highest-end GPT-6 model

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
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

$2 per 1M tokens (input)
Input: $2 per 1 million tokens
Output: $10 per 1 million tokens
Free Version
Free Trial

Pricing

$0.30 per million input tokens
$0.30 per million input tokens and $1.20 per million output tokens
Free Version
Free Trial

Reviews/Ratings

Overall 5.0 / 5
features 5.0 / 5

Reviews/Ratings

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

Pros & Cons from Real Users

Pros

  • What I like most is that it gives me a lot of Astra’s capability without feeling like I am burning premium-model money on every task. I have been using it for coding, agent workflows, research, and larger technical projects where I need strong reasoning but still care about speed and cost. Tool support is another big strength. Sol can work with web search, files, code execution, shell access, computer use, MCP, and function calling, so it feels much more useful as an agent model than something that only generates text.

Cons

  • The only real downside is that when I am dealing with the absolute hardest reasoning problem, I may still step up to Astra. But for most serious day-to-day development and agent work, Sol is the model I would rather run heavily.

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
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

OpenAI
Founded: 2015
United States
openai.com

Company Information

MiniMax
Founded: 2021
Singapore
www.minimax.io

Alternatives

GPT-6 Astra

GPT-6 Astra

OpenAI

Alternatives

GPT-6 Luna

GPT-6 Luna

OpenAI
MiMo-V2.6-Flash

MiMo-V2.6-Flash

Xiaomi Technology
GPT-5.6 Sol

GPT-5.6 Sol

OpenAI
MiniMax

MiniMax

MiniMax AI
MiniMax M1

MiniMax M1

MiniMax

Categories

Categories

Integrations

Hermes Agent
OpenClaw
Pi Agent
Agentforce Vibes
Anuma
Brokk
C#
Doraverse
EaseMate AI
Flowise
HTML
LaunchLemonade
Microsoft 365 Copilot Chat
Microsoft Foundry Models
NextDocs
Ollama
SpawnHQ
Together AI
Verdent
ZeroHuman

Integrations

Hermes Agent
OpenClaw
Pi Agent
Agentforce Vibes
Anuma
Brokk
C#
Doraverse
EaseMate AI
Flowise
HTML
LaunchLemonade
Microsoft 365 Copilot Chat
Microsoft Foundry Models
NextDocs
Ollama
SpawnHQ
Together AI
Verdent
ZeroHuman
Claim GPT-6 Sol and update features and information
Claim GPT-6 Sol and update features and information
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Claim MiniMax M3 and update features and information