Model introduction
MiniMax M3 is MiniMax's next-generation model for million-token context, agents, and office automation, using sparse attention to reduce long-context compute.
Model capabilities
Specifications come from the cited model material. Catalog tags help identify access features; use the source documentation for exact limits.
Verified specifications
- Official positioning
- Long-context agent and office model
- Context window
- 1,000,000 tokens
- Core architecture
- MiniMax Sparse Attention
- Primary workflows
- Agents, documents, spreadsheets, presentations
Sources: B.AI MiniMax M3 model guide
Model pricing and access
Prices are read directly from the MoleAPI console catalog and shown by current billing group and context tier.
Your final charge follows the account group shown in the console.
Live pricing source
Pricing table
USD / 1M tokensStandardx1defaultInput $0.3 · Output $1.2
Input
$0.3 / 1M tokens
Output
$1.2 / 1M tokens
Cache read
$0.06 / 1M tokens
Discountx0.8discountInput $0.24 · Output $0.96
Input
$0.24 / 1M tokens
Output
$0.96 / 1M tokens
Cache read
$0.048 / 1M tokens
Relayx0.3relayInput $0.09 · Output $0.36
Input
$0.09 / 1M tokens
Output
$0.36 / 1M tokens
Cache read
$0.018 / 1M tokens
Temporary (availability may vary)x0.1tempInput $0.03 · Output $0.12
Input
$0.03 / 1M tokens
Output
$0.12 / 1M tokens
Cache read
$0.006 / 1M tokens
Access protocols
Available billing groups: Standard, Discount, Relay, Temporary (availability may vary)
- openai
- POST
- /v1/chat/completions
- openai-response
- POST
- /v1/responses
- anthropic
- POST
- /v1/messages
- gemini
- POST
- /v1beta/models/{model}:generateContent
- openai-response-compact
- POST
- /v1/responses/compact
- openai-alpha-search
- POST
- /v1/alpha/search
Complete model guide
Prepared from vendor sources and independently reviewed. · 2026-07-28
MiniMax M3 model guide
MiniMax M3 is a frontier coding and agentic model built on MiniMax Sparse Attention (MSA) and positioned for long-context workloads. MiniMax officially released M3 on May 31, 2026, with a context window of up to 1 million tokens and native multimodal input support. [6]
Positioning and core capabilities
MiniMax positions M3 for coding, agentic work, tool use, and ultra-long-context processing. The model is designed around MSA, MiniMax’s sparse-attention architecture for reducing the compute demands of long-context inference. [5] [6]
M3 supports text, image, and video input, and MiniMax describes desktop-computer operation as part of its agentic capability set. [6] The model’s published context limit is 1,000,000 total input and output tokens. [8]
Capabilities and specs
MiniMax M3 combines million-token context handling with coding, reasoning, and tool-using agent workflows. MiniMax documents a direct API rate limit of 200 requests per minute and 10,000,000 tokens per minute for M3. [7]
| Specification | Details |
|---|---|
| Context window | 1,000,000 total input and output tokens [8] |
| Input modalities | Text, image, and video [6] |
| Core architecture | MiniMax Sparse Attention (MSA) [6] |
| Primary positioning | Frontier coding and agentic model [5] |
| Direct API rate limit | 200 RPM and 10,000,000 TPM [7] |
MSA uses sparse attention to target more efficient long-context processing than full attention. MiniMax reports that, at a 1 million-token context length, MSA reduces per-token compute relative to its prior-generation model and improves prefill and decoding speed; these are vendor-reported performance results. [6]
Use cases
MiniMax M3 is positioned for large-codebase understanding, multi-document analysis, and long-running tool-using agents. MiniMax also identifies document, spreadsheet, and presentation workflows as target applications. [1] [6]
Its long context is intended to support work across extensive conversation histories, repositories, and document collections. M3’s multimodal input and desktop-operation capabilities extend its positioning to agents that work across text, images, video, and computer interfaces. [6]
Material limitations
MiniMax M3’s 1 million-token limit is a combined input-and-output context limit rather than an input-only allowance. [8]
MiniMax describes M3 as natively multimodal, while third-party platform documentation notes that image-input availability can vary by serving-platform rollout and configuration. [6] [1]
Sources
Code examples
These examples use MoleAPI's Responses API endpoint and run after you replace the API key.
curl https://api.moleapi.com/v1/responses \
-H "Authorization: Bearer $MOLEAPI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "minimax-m3",
"input": "Explain this problem step by step."
}'Frequently asked questions
How is minimax-m3 priced?
This page reads prices from the MoleAPI console API and updates with model prices, context tiers, and account groups.
How can I access minimax-m3?
Protocols and endpoints come from the supported_endpoint_types field in the MoleAPI model catalog.
How do I switch an existing project to minimax-m3?
Keep the MoleAPI API address and key, replace the model parameter with the model ID on this page, then check protocol-specific parameter differences.
Where do the minimax-m3 model details come from?
Capabilities and limitations are checked against B.AI and the other cited pages. Pricing and available protocols come only from the MoleAPI console.