LLM Reference

MiniMax M2.5 Highspeed

Released
2026-02-12
Last refreshed
2026-06-29
Status
Researched 122d ago
Open sourceCommercial use: permittedCodingRAGAgentsLong contextClassificationJSON / Tool use

MiniMax M2.5 Highspeed is worth evaluating for coding, rag, and agents when its provider route and context window match the workload.

Use it for

  • Teams evaluating coding, rag, and agents
  • Workloads that can use a 205k context window
  • Buyers comparing 3 tracked provider routes

Do not use it for

  • Vision or document-understanding workloads
Specifications
Released
2026-02-12
Context
205k
Max output
131,072
Parameters
230B (10B active)
Architecture
Decoder Only
Specialization
general
Openness
Open source
License
MITOSI-approvedCommercial use: permitted
Weights
Unknown
Code
Unknown
Created by

Developing AI for gaming and entertainment.

Minhang, Shanghai, China
Founded 2021
Website
Pricing
Output / 1M
$2.40
Input / 1M
$0.600

Cheapest of 3 routes · Novita AI

About

MiniMax M2.5 Highspeed is MiniMax's inference-optimized variant of M2.5, released simultaneously in February 2026. It delivers identical intelligence and outputs to standard M2.5 through a specialized inference engine at lower latency. The model supports a 204,800-token context window, 131,072-token max output, function calling, structured output, and reasoning. API model ID: MiniMax-M2.5-highspeed. It is designed for latency-sensitive interactive applications and automated agent pipelines.

Top use-case fit: coding, agents, and build tasks

Coding

Q/$ C

1 relevant benchmark in the decision map.

RAG

Included by capability and metadata signals in the decision map.

Agents

Q/$ C

1 relevant benchmark in the decision map.

Provider price ladder

Compare all 3

Compare API pricing across 3 providers for input and output tokens, batch, and cached reads when available.

ProviderInput / 1MOutput / 1MCacheRoute
Novita AI$0.600$2.40-
Serverless
Vercel AI Gateway$0.600$2.40read $0.030
Serverless
MiniMax---
ServerlessPartial

Capabilities

ReasoningJSON / Tool useStructured Outputs

Benchmark peer barsfor Coding

Benchmark scores(1)

Scores are benchmark-specific and are direction-aware: the same numeric gap can mean very different outcomes across suites. Use the leaderboard context and this model's provider route to decide whether the winning margin is meaningful for your workload.
BenchmarkScoreVersionEvaluationSource
SWE-bench Verified80.2M2 (resolved%)Observed 2026-06-07—Source

Migration checks

No linked migration route is available for this model yet.