What input types does MiniMax M3 accept?

Text, image, and video input. Output is text. Multimodality is native to MiniMax M3 rather than added through a separate vision adapter.

What is the context window for MiniMax M3?

MiniMax M3 supports a context window of 1.0M tokens and a max output of 1.0M tokens per request.

How does MiniMax M3 compare to M2.7?

M2.7 focuses on multi-agent orchestration, dynamic tool search, and text-only enterprise workflows. MiniMax M3 extends the series with native multimodal input, the 1.0M tokens context window, and the MSA architecture for long-context efficiency.

Is there a faster variant of MiniMax M3?

Yes. Select `minimax/minimax-m3-highspeed` where your provider exposes it. The highspeed variant targets higher throughput with the same output behavior.

Does MiniMax M3 support automatic prompt caching?

Yes. Automatic prompt caching is enabled by default, which reduces effective cost on repeated context patterns. $0.06 per million cached input tokens applies where the provider exposes a cached rate.

How do I access MiniMax M3 through the AI SDK?

Set the model identifier to `minimax/minimax-m3` in your AI SDK configuration. AI Gateway routes the request across the providers serving MiniMax M3 with configurable failover.

Is Zero Data Retention available for MiniMax M3?

Yes, Zero Data Retention is available for this model. Zero Data Retention is offered on a per-provider basis. See https://vercel.com/docs/ai-gateway/capabilities/zdr for details.

MiniMax

MiniMax M3

MiniMax M3 is MiniMax's first model with a 1.0M tokens context window and native multimodal input. It targets software engineering, terminal-based tool use, and agentic web browsing, with a max output of 1.0M tokens per request.

View API reference

Input and output price: Prices from: Input $0.26, Output $1.02, Per 1M tokens
24h uptime: Loading AI Gateway uptime

Get API key Read the docs

import { streamText } from 'ai'

const result = streamText({
  model: 'minimax/minimax-m3',
  prompt: 'Why is the sky blue?'
})

Read docs

Overview Playground Providers Uptime Status Throughput Latency API Similar About FAQ

Copy link to headingPlayground

Try out MiniMax M3 by MiniMax. Usage is billed to your team at API rates. Free users (those who haven't made a payment) get $5 of credits every 30 days.

MiniMax M3

Copy link to headingProviders

Route requests across multiple providers. Copy a provider slug to set your preference. Visit the docs for more info. Using a provider means you agree to their terms, listed under Legal.

Provider

Context	Max Output	Latency	Throughput	Input	Output	Cache	Web Search	Capabilities	ZDR	No Training	Free Tier	Release Date

MiniMax

50% off

Legal:Terms•Privacy

0.8 s

105 tps

$0.30/M+1 more

$1.20/M+1 more

Read$0.06/M

—

05/31/2026

Fireworks

Legal:Terms•Privacy

512K

1.0 s

176 tps

$0.30/M

$1.20/M

Read$0.06/M

—

05/31/2026

Nebius

Legal:Terms•Privacy

1.0 s

62 tps

$0.30/M

$1.20/M

—

05/31/2026

GMICloud

Legal:Terms•Privacy

0.8 s

37 tps

$0.60/M+1 more

$2.40/M+1 more

Read$0.12/M

—

05/31/2026

Morph

Legal:Terms•Privacy

256K

0.8 s

277 tps

$0.26/M

$1.02/M

—

05/31/2026

Getting started

Call MiniMax M3 through AI Gateway with the AI SDK generateText and streamText functions, or through the OpenAI Chat Completions, OpenAI Responses, and Anthropic Messages APIs by changing the base URL. AI Gateway authenticates the request and routes it to an available provider.

Install the AI SDK (pnpm add ai dotenv), create an API key from the API Keys page, and set it as AI_GATEWAY_API_KEY in your environment. Full setup is covered in the text generation quickstart.

index.ts

import { generateText } from 'ai';
import 'dotenv/config';

async function main() {
  const result = await generateText({
    model: 'minimax/minimax-m3',
    prompt: 'Why is the sky blue?',
  });

  console.log(result.text);
}

main().catch(console.error);

Top-level parameters

The same MiniMax M3 request in each API format AI Gateway supports.

top-level-params.ts

import { generateText } from 'ai';
import 'dotenv/config';

async function main() {
  const result = await generateText({
    model: 'minimax/minimax-m3',
    system: 'You are a concise technical assistant.',
    prompt: 'Summarize the tradeoffs between static generation and SSR.',
    maxOutputTokens: 1024,
  });

  console.log(result.text);
}

main().catch(console.error);

Standard parameters like prompt, messages, temperature, and tools work as documented in the AI SDK docs. These are the parameters with model-specific behavior.

Parameter	Type	Required	Description
`model`	`string`	Yes	Model ID in the form `creator/model`, e.g. `minimax/minimax-m3`. AI Gateway routes the request to an available provider.
`maxOutputTokens`	`number`	No	Hard cap on generated tokens. MiniMax M3 supports up to `1,049,000` output tokens. Reasoning tokens count toward this limit.
`reasoning`	`'provider-default' \| 'none' \| 'minimal' \| 'low' \| 'medium' \| 'high' \| 'xhigh'`	No	Provider-agnostic reasoning effort, available in AI SDK 7 or later. Maps to the provider’s native reasoning configuration; reasoning settings under `providerOptions` take precedence when both are set. See the Reasoning section below.
`providerOptions`	`Record<string, JSONValue>`	No	AI Gateway routing options under `gateway`, plus any provider-native options under the provider’s own namespace — see the table below.

Input limits

Input	Formats	Sources	Max count	Max size	Limits
Text	—	—	—	—	Prompt and response share the 1M-token context window
Image	—	URL, base64, Uint8Array	—	—	Sent as image parts in messages; counts as input tokens
PDF	—	URL, base64, Uint8Array	—	—	Sent as file parts in messages; counts as input tokens

Provider options

Set AI Gateway routing options under providerOptions.gateway. For provider-specific options, pass them under the provider’s namespace as documented by the AI SDK.

Learn more in the AI SDK provider docs.

provider-options.ts

import { generateText } from 'ai';
import 'dotenv/config';

async function main() {
  const result = await generateText({
    model: 'minimax/minimax-m3',
    prompt: 'Why is the sky blue?',
    providerOptions: {
      gateway: {
        only: ['minimax', 'fireworks'],
      },
    },
  });

  console.log(result.text);
}

main().catch(console.error);

These AI Gateway routing options apply to every model. Provider-specific options pass through under the provider’s own namespace (for example providerOptions.anthropic) exactly as documented by the AI SDK.

Parameter	Type	Required	Description
`providerOptions.gateway.only`	`string[]`	No	Restrict routing to these provider slugs. Requests fail over only within the listed providers.
`providerOptions.gateway.order`	`string[]`	No	Preferred provider order. Listed providers are tried first; unlisted providers remain available as fallbacks.
`providerOptions.gateway.sort`	`'cost' \| 'ttft' \| 'tps'`	No	Rank candidate providers by price, time to first token, or tokens per second instead of the default routing order.
`providerOptions.gateway.zeroDataRetention`	`boolean`	No	Route only to providers with a zero-data-retention policy for this model.

Routing across providers

AI Gateway serves the same model through multiple providers and fails over automatically. order expresses a preference while keeping every provider eligible; only is a hard allowlist — if none of the listed providers are available the request fails instead of falling back.

Options under a provider's own namespace (for example providerOptions.anthropic) are forwarded to that provider with the request. Providers ignore option namespaces that don't apply to them, so it is safe to set provider options alongside gateway routing options.

Reasoning

AI Gateway bridges reasoning across every API format. The AI SDK exposes a provider-agnostic top-level reasoning level (none, minimal, low, medium, high, or xhigh); the Chat Completions and Responses formats take the same effort under reasoning.effort; and the Anthropic Messages format uses a native thinking token budget. Whichever you send, the gateway maps it to the target model’s native configuration, converting between effort levels and token budgets as needed. Reasoning-related settings under providerOptions take full precedence over the top-level reasoning value and are never merged. Reasoning tokens typically count toward your output-token usage, though how they’re reported and billed varies by provider.

Learn more in the AI Gateway reasoning guide.

reasoning.ts

import { generateText } from 'ai';
import 'dotenv/config';

async function main() {
  const result = await generateText({
    model: 'minimax/minimax-m3',
    prompt: 'Explain the Monty Hall problem step by step.',
    reasoning: 'high',
  });

  console.log(result.text);
}

main().catch(console.error);

Image input

Send images alongside text as message parts. Images count as input tokens.

image-input.ts

import { generateText } from 'ai';
import 'dotenv/config';

async function main() {
  const result = await generateText({
    model: 'minimax/minimax-m3',
    messages: [
      {
        role: 'user',
        content: [
          { type: 'text', text: 'Describe this image.' },
          { type: 'image', image: 'https://example.com/photo.jpg' },
        ],
      },
    ],
  });

  console.log(result.text);
}

main().catch(console.error);

PDF input

Attach PDFs as file parts. Their contents count as input tokens.

pdf-input.ts

import { generateText } from 'ai';
import 'dotenv/config';

async function main() {
  const result = await generateText({
    model: 'minimax/minimax-m3',
    messages: [
      {
        role: 'user',
        content: [
          { type: 'text', text: 'Summarize this document.' },
          {
            type: 'file',
            mediaType: 'application/pdf',
            data: 'https://example.com/document.pdf',
          },
        ],
      },
    ],
  });

  console.log(result.text);
}

main().catch(console.error);

Tool calling

Expose tools the model can call. Define each tool’s inputs with a Zod schema.

tool-calling.ts

import { generateText, tool } from 'ai';
import { z } from 'zod';
import 'dotenv/config';

async function main() {
  const result = await generateText({
    model: 'minimax/minimax-m3',
    prompt: 'What is the weather in San Francisco?',
    tools: {
      getWeather: tool({
        description: 'Get the current weather for a location',
        inputSchema: z.object({ location: z.string() }),
        execute: async ({ location }) => ({ location, temperatureC: 18 }),
      }),
    },
  });

  console.log(result.text);
}

main().catch(console.error);

Copy link to headingMore models by MiniMax

Model

Context	Latency	Throughput	Input	Output	Cache	Web Search	Capabilities	Providers	ZDR	No Training	Free Tier	Release Date

minimax/minimax-m2.7

205K

1.0 s

61 tps

$0.30/M+1 more

$1.20/M+1 more

Read$0.06/M

Write$0.38/M

—

03/18/2026

minimax/minimax-m2.7-highspeed

205K

0.9 s

65 tps

$0.60/M

$2.40/M

Read$0.06/M

Write$0.38/M

—

03/18/2026

minimax/minimax-m2.5

0.6 s

82 tps

$0.27/M+1 more

$0.95/M+1 more

Read$0.03/M

Write$0.38/M

—

02/12/2026

minimax/minimax-m2.5-highspeed

205K

0.9 s

82 tps

$0.60/M

$2.40/M

Read$0.03/M

Write$0.38/M

—

02/12/2026

minimax/minimax-m2.1

205K

0.8 s

106 tps

$0.30/M

$1.20/M

Read$0.03/M

Write$0.38/M

—

12/23/2025

minimax/minimax-m2

205K

0.8 s

82 tps

$0.30/M

$1.20/M

Read$0.03/M

Write$0.38/M

—

10/27/2025

Copy link to headingAbout MiniMax M3

MiniMax M3 is built around MiniMax Sparse Attention (MSA), an attention variant that splits the key-value cache into blocks and pre-filters which blocks contribute to each query. That design supports the 1.0M tokens context window without the quadratic compute scaling of full attention, and it lets MiniMax M3 keep prefill and decode efficient on long inputs.

Native multimodality is wired in from the start of training rather than bolted on later. MiniMax M3 accepts text, image, and video input and produces text output. The pretraining pipeline aligns visual and textual semantics directly, which carries over to multimodal coding tasks like analyzing a screenshot of a failing test and writing a patch, or reproducing a bug from a GitHub issue thread.

MiniMax M3 is positioned for software engineering, terminal-based tool use, and agentic web browsing. It scores 59.0% on SWE-Bench Pro and 70.06% on OSWorld-Verified for computer use. Automatic prompt caching is enabled by default, which reduces effective cost on repeated context patterns common in agent loops.

Copy link to headingWhat To Consider When Choosing a Provider

Configuration: MiniMax M3 pairs the 1.0M tokens context window with native image and video input, which makes it a fit for workflows that reason over screenshots, design references, or long video transcripts alongside code. Route through AI Gateway via the AI SDK plus Chat Completions / Responses / Messages APIs to get provider failover, observability, and unified pricing across the providers serving MiniMax M3.
Zero Data Retention: Zero Data Retention is available for this model. It is offered on a per-provider and model basis. See the documentation for details.
Authentication: AI Gateway authenticates requests using an API key or OIDC token. You do not need to manage provider credentials directly.

Copy link to headingWhen to Use MiniMax M3

Best for

Long-horizon coding agents: Sessions that span an entire repository without fragmenting context across requests
Multimodal engineering: Workflows that reason over screenshots, diagrams, or video alongside code
Computer-use agents: Browser and desktop automation that benefits from strong OSWorld performance
Terminal-driven tool chains: Agents that read command output and iterate across many steps
Long-video and long-document understanding: Tasks that require sustained attention over hours of input

Consider alternatives when

Raw inference speed: Latency matters more than capability breadth, so consider M3-highspeed
Short single-turn text tasks: A smaller model is cheaper when the workload is single-turn and text-only
Text-only reasoning: Standard M2.7 covers the use case at lower cost when multimodal input is not needed

Copy link to headingConclusion

MiniMax M3 brings a 1.0M tokens context window, native multimodal input, and agentic coding capability into one model. For teams running long-horizon agents over full repositories, browser sessions, or video input, MiniMax M3 reduces the need to split work across multiple specialized models. Route it through AI Gateway via the AI SDK plus Chat Completions / Responses / Messages APIs for failover and unified observability.

Copy link to headingFrequently Asked Questions

What is MiniMax Sparse Attention?
MSA is the attention variant behind MiniMax M3. It splits the key-value cache into blocks and pre-filters which blocks contribute to each query, which keeps compute manageable at the 1.0M tokens context length.
What input types does MiniMax M3 accept?
Text, image, and video input. Output is text. Multimodality is native to MiniMax M3 rather than added through a separate vision adapter.
What is the context window for MiniMax M3?
MiniMax M3 supports a context window of 1.0M tokens and a max output of 1.0M tokens per request.
How does MiniMax M3 compare to M2.7?
M2.7 focuses on multi-agent orchestration, dynamic tool search, and text-only enterprise workflows. MiniMax M3 extends the series with native multimodal input, the 1.0M tokens context window, and the MSA architecture for long-context efficiency.
Is there a faster variant of MiniMax M3?
Yes. Select minimax/minimax-m3-highspeed where your provider exposes it. The highspeed variant targets higher throughput with the same output behavior.
Does MiniMax M3 support automatic prompt caching?
Yes. Automatic prompt caching is enabled by default, which reduces effective cost on repeated context patterns. $0.06 per million cached input tokens applies where the provider exposes a cached rate.
How do I access MiniMax M3 through the AI SDK?
Set the model identifier to minimax/minimax-m3 in your AI SDK configuration. AI Gateway routes the request across the providers serving MiniMax M3 with configurable failover.
Is Zero Data Retention available for MiniMax M3?
Yes, Zero Data Retention is available for this model. Zero Data Retention is offered on a per-provider basis. See https://vercel.com/docs/ai-gateway/capabilities/zdr for details.

Your use is subject to MiniMax's Terms & Privacy Policies.

Agent Stack

Core Platform

Tools

Learn

Build

Explore

MiniMax M3

Copy link to headingPlayground

Copy link to headingProviders

Copy link to headingUptime24 hours

Copy link to headingThroughput24 hours

Copy link to headingLatency24 hours

Getting started

Top-level parameters

Input limits

Provider options

Routing across providers

Reasoning

Image input

PDF input

Tool calling

Copy link to headingMore models by MiniMax

Copy link to headingAbout MiniMax M3

Copy link to headingWhat To Consider When Choosing a Provider

Copy link to headingWhen to Use MiniMax M3

Best for

Consider alternatives when

Copy link to headingConclusion

Copy link to headingFrequently Asked Questions