MiniMax M3.1 Flash
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Description
MiniMax M2.5 is a next-generation foundation model built to power complex, economically valuable tasks with speed and cost efficiency. Trained using large-scale reinforcement learning across hundreds of thousands of real-world task environments, it excels in coding, tool use, search, and professional office workflows. In programming benchmarks such as SWE-Bench Verified and Multi-SWE-Bench, M2.5 reaches state-of-the-art levels while demonstrating improved multilingual coding performance. The model exhibits architect-level reasoning, planning system structure and feature decomposition before writing code. With throughput speeds of up to 100 tokens per second, it completes complex evaluations significantly faster than earlier versions. Reinforcement learning optimizations enable more precise search rounds and fewer reasoning steps, improving overall efficiency. M2.5 is available in two variants—standard and Lightning—offering identical capabilities with different speed configurations. Pricing is designed to be dramatically lower than competing frontier models, reducing cost barriers for large-scale agent deployment. Integrated into MiniMax Agent, the model supports advanced office skills including Word formatting, Excel financial modeling, and PowerPoint editing. By combining high performance, efficiency, and affordability, MiniMax M2.5 aims to make agent-powered productivity accessible at scale.
Description
MiniMax M3.1 Flash is an advanced hosted language model designed specifically for developers who are creating coding assistants, AI agents, and various software applications. It can be accessed via MiniMax's API and MiniMax Code, allowing it to process inputs in text, image, and video formats while generating relevant text responses. Among its documented applications are functionalities such as code generation, debugging, complex reasoning tasks, tool utilization, analysis of codebases and documents, as well as enhancing computer workflows. The API boasts an impressive context window that can handle up to 1 million tokens, offers adjustable reasoning capabilities, and supports request formats that are compatible with both OpenAI and Anthropic standards. Charges for usage are based on the number of tokens used for input, output, and cached input. Comprehensive documentation is provided by MiniMax to assist with API integration and effective model utilization. M3.1 Flash is accessible through the hosted API, M Plan, and MiniMax Code, while there are plans to release model weights in the future, expanding its potential applications even further. This innovation represents a significant step forward in the integration of AI into software development processes.
API Access
Has API
Yes
API Access
Has API
Yes
Integrations
APIFree
Yes
Alibaba AI Coding Plan
Yes
BLACKBOX AI
Yes
Claude Code
Yes
Clawd.run
Yes
Cline
Yes
Fireworks AI
Yes
Kilo Code
Yes
Ollama
Yes
OpenClaw
Yes
Integrations
APIFree
Yes
Alibaba AI Coding Plan
Yes
BLACKBOX AI
Yes
Claude Code
Yes
Clawd.run
Yes
Cline
Yes
Fireworks AI
Yes
Kilo Code
Yes
Ollama
Yes
OpenClaw
Yes
Pricing Details
Free
Open source
Free Trial
No
Free Version
Yes
Pricing Details
$0.15/1M input tokens
Input: $0.15 per 1 million tokens; output: $0.60 per 1 million tokens; cached input: $0.015 per 1 million tokens. Standard pay-as-you-go billing in USD, based on token usage.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
MiniMax
Founded
2021
Country
Singapore
Website
www.minimax.io
Vendor Details
Company Name
MiniMax
Founded
2022
Country
China
Website
www.minimax.io/blog/minimax-m31f