models

MiniMax: MiniMax M3.1 Flash

Markdown · JSON

MiniMax: MiniMax M3.1 Flash

minimax/minimax-m3.1-flash
MiniMaxTextInput from $0.00015 / 1KOutput from $0.0006 / 1K

MiniMax M3.1 Flash helps analyze documents, write code and plan multistep tasks; Standard also accepts image input through Chat Completions and Responses.

MiniMax M3.1 Flash is a MiniMax model released on October 19, 2026 for programming, reasoning and tasks involving several connected steps. The developer emphasizes document consistency, action planning and software development. The model also supports multimodal understanding; the input type available in Ailoot API depends on the selected method.

Tasks you can assign

  • Read a large technical brief, identify dependencies and prepare an implementation plan.
  • Analyze code, explain a possible cause of an error and propose a fix with a verification method.
  • Compare several documents, consolidate shared requirements and note discrepancies in the source data.
  • Prepare instructions, an analytical memo or a draft report with a consistent structure.

The official material specifically discusses long development sequences: understanding source code, implementing a change, fixing bugs and verifying with tests. In a text conversation, organize this into stages: first request a plan, then a specific change, followed by an explanation and verification criteria.

Text and images

In Standard, images can be supplied through Chat Completions and Responses together with a text question. For example, ask the model to analyze a screenshot’s contents, connect a visible element to a problem description or incorporate information from an image into a text conclusion. Specify which part of the image matters and what result you need.

In Ultra and through this listing’s Gemini-compatible method, the input is text. All variants return text: an explanation, an action list, analysis or code. For document comparison and report preparation, define the result’s structure in advance and ask the model to distinguish information from the supplied material from its proposed conclusions.

Reasoning and long context

MiniMax M3.1 Flash performs reasoning before producing its final answer. The developer’s documentation specifies depth levels from low to max; reasoning remains enabled. Define the final response format separately: detailed internal reasoning and a long user-facing text are different requirements.

In Standard, the context window is up to 1,000,000 tokens. It supports long text material, code and discussion history within the chosen request’s limits. Provide source names, their order and the questions to answer; for a substantial result, divide the task into clear stages and retain intermediate decisions in subsequent messages.

Available through Ailoot API

Core OpenAI ResponsesPOST /v1/responses
Input types
text, image
Output types
text
Context
1,000,000 tokens
Max. output
524,288 tokens
Input
$0.00015 / 1K
Output
$0.0006 / 1K
Cache read
≈$0.000015 / 1K
Cache write
$0.0003 / 1K
Cache write, 5 min
$0.0003 / 1K tokens
Core OpenAI ChatPOST /v1/chat/completions
Input types
text, image
Output types
text
Context
1,000,000 tokens
Max. output
524,288 tokens
Input
$0.00015 / 1K
Output
$0.0006 / 1K
Cache read
≈$0.000015 / 1K
Cache write
$0.0003 / 1K
Cache write, 5 min
$0.0003 / 1K tokens
Core Gemini generateContentPOST /v1beta/models/{model}:generateContent
Input types
text
Output types
text
Context
1,000,000 tokens
Max. output
524,288 tokens
Input
$0.00015 / 1K
Output
$0.0006 / 1K
Cache read
≈$0.000015 / 1K
Cache write
$0.0003 / 1K
Cache write, 5 min
$0.0003 / 1K tokens
Ultra OpenAI ChatPOST /v1/chat/completions
Input types
text
Output types
text
Context
968,576 tokens
Max. output
80,000 tokens
Input
$0.0003 / 1K
Output
$0.0012 / 1K
Cache read
≈$0.00003 / 1K
Cache write
≈$0.000036 / 1K
Cache write, 5 min
≈$0.000036 / 1K tokens
Ultra OpenAI ResponsesPOST /v1/responses
Input types
text
Output types
text
Context
968,576 tokens
Max. output
80,000 tokens
Input
$0.0003 / 1K
Output
$0.0012 / 1K
Cache read
≈$0.00003 / 1K
Cache write
≈$0.000036 / 1K
Cache write, 5 min
≈$0.000036 / 1K tokens
Ultra Gemini generateContentPOST /v1beta/models/MiniMax-M3.1-Flash:generateContent
Input types
text
Output types
text
Context
968,576 tokens
Max. output
80,000 tokens
Input
$0.0003 / 1K
Output
$0.0012 / 1K
Cache read
≈$0.00003 / 1K
Cache write
≈$0.000036 / 1K
Cache write, 5 min
≈$0.000036 / 1K tokens
Ultra Anthropic MessagesPOST /v1/messages
Input types
text
Output types
text
Context
Not specified in the catalogue
Max. output
Not specified in the catalogue
Input
$0.0003 / 1K
Output
$0.0012 / 1K
Cache read
≈$0.00003 / 1K
Ultra OpenAI ResponsesPOST /v1/responses
Input types
text
Output types
text
Context
Not specified in the catalogue
Max. output
Not specified in the catalogue
Input
$0.0003 / 1K
Output
$0.0012 / 1K
Cache read
≈$0.00003 / 1K
Ultra OpenAI ChatPOST /v1/chat/completions
Input types
text
Output types
text
Context
Not specified in the catalogue
Max. output
Not specified in the catalogue
Input
$0.0003 / 1K
Output
$0.0012 / 1K
Cache read
≈$0.00003 / 1K
Ultra Gemini generateContentPOST /v1beta/models/minimax/minimax-m3.1-flash:generateContent
Input types
text
Output types
text
Context
Not specified in the catalogue
Max. output
Not specified in the catalogue
Input
$0.0003 / 1K
Output
$0.0012 / 1K
Cache read
≈$0.00003 / 1K
minimax/minimax-m3.1-flash · JSON
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In a text conversation, organize this into stages: first request a plan, then a specific change, followed by an explanation and verification criteria.\n\n### Text and images\n\nIn Standard, images can be supplied through Chat Completions and Responses together with a text question. For example, ask the model to analyze a screenshot’s contents, connect a visible element to a problem description or incorporate information from an image into a text conclusion. Specify which part of the image matters and what result you need.\n\nIn Ultra and through this listing’s Gemini-compatible method, the input is text. All variants return text: an explanation, an action list, analysis or code. For document comparison and report preparation, define the result’s structure in advance and ask the model to distinguish information from the supplied material from its proposed conclusions.\n\n### Reasoning and long context\n\nMiniMax M3.1 Flash performs reasoning before producing its final answer. The developer’s documentation specifies depth levels from low to max; reasoning remains enabled. Define the final response format separately: detailed internal reasoning and a long user-facing text are different requirements.\n\nIn Standard, the context window is up to 1,000,000 tokens. It supports long text material, code and discussion history within the chosen request’s limits. 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Questions

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