MiniMax-M3 API
$0.494 - 0.988(~ 33.6 - 67.2 credits) per 1M input tokens; $1.976 - 3.953(~ 134.4 - 268.8 credits) per 1M output tokens
$0.618 - 1.235(~ 42 - 84 credits) per 1M cache write tokens; $0.099 - 0.197(~ 6.7 - 13.4 credits) per 1M cache read tokens
Context over 512K tokens is billed at 2× the official rate (long-context tier, not discounted). Supports thinking, multimodal input (image/video/PDF) and prompt caching.
Stable managed access for production workloads. Recommended when you need dashboard billing, API key control, and predictable integration behavior.
Use the same API endpoint for all versions. Only the model parameter differs.
MiniMax-M3 API
Route MiniMax-M3 through EvoLink for coding agents, repo Q&A, research, and multimodal document analysis with a ~1M context window, deep thinking, and prompt caching. Connect via OpenAI-compatible or Anthropic Messages endpoints, with pricing from $0.49/1M input tokens.
Access and workflow fit
Best fit
Coding agents
Model ID
MiniMax-M3
Access
OpenAI + Anthropic
Context
1M window
Input
$0.49/1M
Built-in
Thinking + multimodal + caching
What can you build with the MiniMax-M3 API?
Coding Agents & Claude Code Workflows
Build coding copilots and agents that handle repo Q&A, code generation, and review. Because MiniMax-M3 exposes a native Anthropic Messages endpoint, it drops into Claude Code-style CLIs and agent frameworks, while deep thinking handles multi-step reasoning in a single API.
Multimodal Understanding
Feed images, video, and PDF documents directly into MiniMax-M3 alongside text. Use it for visual Q&A, screenshot-to-code, chart and document understanding, and video summarization without wiring a separate vision model into your stack.
Long-Context Document Processing
Process contracts, reports, codebases, and large knowledge bases without aggressive chunking. The ~1M context window suits structured summaries, extraction pipelines, and comparison tasks, while prompt caching keeps repeated long prefixes affordable.
Why teams choose the MiniMax-M3 API
Teams choose MiniMax-M3 on EvoLink when they need long-context multimodal reasoning, dual-protocol access, and predictable token pricing without building a vendor-specific integration.
Dual-endpoint access
Call MiniMax-M3 through the OpenAI-compatible endpoint or the native Anthropic Messages endpoint with one EvoLink key. Existing OpenAI SDK code and Claude Code-style clients both work without rebuilding your integration path.
Predictable production cost
Visible token pricing makes budgeting easier: input from $0.49/1M, output from $1.98/1M, and cache reads from about $0.10/1M for repeated prompts. Context above 512K is billed at a 2× long-context tier.
Thinking, multimodal, and caching
Use ~1M context for large prompts, enable deep thinking for complex reasoning, pass image/video/PDF input directly, and rely on prompt caching to cut the cost of repeated context.
MiniMax-M3 vs MiniMax-M2.5: which model should you use?
Use this as a model selection guide, not a benchmark claim. M2.5 remains useful as a lower-cost MiniMax-family fallback, while M3 is the stronger choice for more demanding agentic and multimodal workloads.
| Decision point | MiniMax-M2.5 | MiniMax-M3 |
|---|---|---|
| Model role | Lower-cost MiniMax fallback for text-heavy workloads | Primary MiniMax option for advanced agentic workloads |
| Best fit | Repo Q&A, document analysis, research, and cost-sensitive text tasks | Coding agents, Claude Code-style CLIs, multimodal reasoning, and full-repo analysis |
| Context window | 204K context | ~1M context with a 2x tier above 512K |
| Input coverage | Text-focused model with web search and prompt caching | Text plus image, video, and PDF input with thinking and caching |
| Endpoint fit | OpenAI-compatible access | OpenAI-compatible plus native Anthropic Messages access |
| Cost posture | Use when unit cost matters more than peak capability | Use when stronger reasoning, longer context, or multimodal input justify the upgrade |
How to integrate the MiniMax-M3 API
Keep your existing OpenAI or Anthropic client, point it to EvoLink, set the model to MiniMax-M3, and use the same route for coding-agent, multimodal, and long-context workflows.
Step 1 — Authenticate
Create an EvoLink API key and set the EvoLink base URL. Use Bearer auth for the OpenAI-compatible endpoint, or x-api-key for the Anthropic Messages endpoint.
Step 2 — Set required fields
Send `model: MiniMax-M3` with your `messages` array. Reuse stable system prompts and prefixes to benefit from prompt caching on repeated workloads.
Step 3 — Tune outputs
Adjust temperature, top_p, max_tokens, and stream as usual. Enable `thinking` for deep reasoning, and attach images, video, or PDF content blocks for multimodal requests.
MiniMax-M3 API features for production teams
Concrete controls and deployment signals instead of a generic model overview
Deep thinking mode
Enable thinking for math, logic, and complex multi-step analysis. Reasoning is exposed as a separate field or content block, so you can show or hide the chain of thought in your product.
~1M Context Window
Fit entire codebases, long documents, and multi-turn context into one request before reaching for aggressive chunking or multi-pass orchestration.
Multimodal input
Pass image, video, and PDF inputs alongside text for visual Q&A, document understanding, and video summarization in the same text API.
OpenAI + Anthropic compatible
Connect with the OpenAI SDK via /v1/chat/completions or the Anthropic SDK via /v1/messages by changing the base URL and model name — no integration rebuild required.
Prompt Caching
Repeated prefixes and system prompts are billed at a lower cache-read rate, which helps recurring agent workflows and high-volume production traffic.
Long-context tier pricing
Requests up to 512K context use the base rate; above 512K, tokens are billed at a 2× long-context tier, so cost scales predictably with prompt size.
MiniMax-M3 API FAQs
Everything you need to know about the product and billing.