MiniMax M3.1 Flash
Neural Network
MiniMax M3.1 Flash is a multimodal model for agentic tasks, coding, and cybersecurity, available via API.
Specifications
- Input
- text, images, documents
- Output
- text
- Context size
- 1 000 000 tokens
- Max answer length
- 524 288 tokens
- Reasoning effort
- low, medium, high, extra high, max
- Capabilities
- reasoning, function calling
How it works MiniMax M3.1 Flash?
MiniMax M3.1 Flash is a multimodal model from MiniMax for complex, multi-step tasks. Benchmarks show significant improvements over M3 in agentic scenarios, programming, and cybersecurity. It is a tool for cases requiring a chain of steps rather than a single response: breaking down tasks, using tools, and verifying results. Via BotHub, the model is accessible from Russia without a VPN or foreign card; payment is in rubles via Russian cards, charged per used token, which do not expire. With over 250 models in one window, you can compare responses in a few clicks. A unified OpenAI-compatible API allows switching models without rewriting integrations. Chats are encrypted via AES-GCM, data is not stored, and companies have access to contracts, invoices, EDI, and an admin panel with limits. Use cases: building agents for internal processes, writing and refactoring code, analyzing logs and debugging, checking security configurations and hypotheses, analyzing data, and preparing technical documentation.Frequently asked questions about MiniMax M3.1 Flash
You can use generated results for commercial purposes. You own all rights to the content you create. The only restriction: make sure your prompt does not include copyrighted third-party material. You are responsible for respecting the rights to any input data.
This is a MiniMax text model with a one-million token context window. It analyzes long documents and code repositories, writes and refactors code, finds bugs, answers questions based on uploaded files and images, reasons through math and logic problems, and calls external functions.
The output limit is up to 524,288 tokens, meaning the model can generate very voluminous text in a single response: detailed technical analysis, large code modules, or full documentation. Breaking tasks into dozens of small requests is usually unnecessary.
Yes, the model has a reasoning mode: it builds a chain of steps before the final answer. This significantly helps with tasks where logic is important—math, STEM, code debugging, and resolving contradictions in long documents.
Yes, the model supports function calling and structured JSON output, making it convenient to use as the core of an agent or pipeline. In BotHub, it is available via a unified OpenAI-compatible API: switching models does not require rewriting integrations.
In addition to text, it accepts images and documents: you can ask it to describe an image, extract data from a screenshot or table, or analyze a large file. Audio and video are not listed in our data—for those, it is better to choose a specialized model from the catalog.
We do not have data on supported languages, so we make no promises in advance—it is easier to test it with your own task in one window and compare it with another model if necessary. The service itself works without a VPN or foreign card, and payment is in rubles.