← Models

MiniMax M2.7

MiniMax · MiniMax M

MiniMax's M2.7 agentic productivity model for coding, office workflows, tool use, and low-cost long-context execution.

Part of MiniMax M family · Other versions: MiniMax M3 , MiniMax M2.5 , MiniMax-M2.5
Type
language
Context
205K tokens
Max Output
N/A
Status
current
Input
$0.3/1M tok
Output
$1.2/1M tok
API Access
Yes
License
proprietary
chinese coding agentic tool-use long-context cost-efficient
Released March 2026 · Updated July 10, 2026

Overview

Freshness note: Model capabilities, limits, and pricing can change quickly. This profile is a point-in-time snapshot last verified on July 10, 2026.

MiniMax M2.7 is an active older M-series productivity model in MiniMax’s public API lineup. It follows M2.5 and keeps the same basic value proposition: inexpensive hosted intelligence for coding, tool use, office-style deliverables, and long-running agent workflows. MiniMax M3 is now the family flagship, adding a 1M context, multimodal input, and public weights.

The March 18 launch frames M2.7 around recursive self-improvement and agent harness work. More concretely, MiniMax now documents M2.7 across release notes, its model overview, pay-as-you-go pricing, token plans, and rate limits, establishing it as an active production route.

Capabilities

MiniMax positions M2.7 for complex agentic productivity tasks. The official model overview highlights top real-world engineering, professional office delivery, and character-rich interaction, while the launch post emphasizes agent harnesses, complex skills, dynamic tool search, and self-improving workflows.

That makes it most relevant for coding agents, office-document automation, research assistants, and low-cost long-context loops where a premium western model would be overkill or too expensive to run continuously.

Technical Details

Public anchors at this snapshot:

  • Standard model ID: MiniMax-M2.7.
  • High-speed sibling: MiniMax-M2.7-highspeed, documented as the same capability with faster inference.
  • API overview lists a 204,800 total-token maximum for M2.7.
  • Text API rate limits list 500 RPM and 20,000,000 TPM for M2.7 and M2.7-highspeed.
  • MiniMax provides OpenAI-compatible and Anthropic-compatible integration paths.

The 204,800 figure is a total input-plus-output budget, not a separate generation ceiling. Here, maxOutput: 0 means that MiniMax does not publish a distinct output-only cap for this route.

Pricing & Access

MiniMax’s current pay-as-you-go pricing lists:

  • MiniMax-M2.7 input: $0.30 per 1M tokens.
  • MiniMax-M2.7 output: $1.20 per 1M tokens.
  • Prompt cache read: $0.06 per 1M tokens.
  • Prompt cache write: $0.375 per 1M tokens.

M2.7-highspeed doubles token prices to 0.60inputand0.60 input and 2.40 output per 1M tokens while targeting faster inference. MiniMax also offers subscription-style token plans with request quotas for standard and high-speed M2.7 routes.

Best Use Cases

Choose MiniMax M2.7 for cost-sensitive text-only coding agents, office workflow automation, long-context document work, and Chinese-English productivity assistants with pinned integrations. Start new family evaluations with M3 unless M2.7’s established text-only route or high-speed sibling is the better operational fit.

It is less ideal when governance, documentation maturity, western enterprise procurement, or a broad app ecosystem matter more than price-performance.

Comparisons

  • MiniMax M3 (MiniMax): Current 1M-context multimodal flagship with public weights; M2.7 remains the smaller-context hosted predecessor.
  • MiniMax M2.5 (MiniMax): Older M-series production tier; M2.7 remains the stronger pinned text-only route.
  • DeepSeek V4 (DeepSeek): Similar low-cost Chinese API alternative with broader 1M-context positioning; M2.7 leans more explicitly into agentic productivity and office workflows.