Sulat.com
AI models
$10 off the fastest DeepSeek V4.1 Flash, Kimi K3 and GLM 5.3 from Synthetic
Meganova logo

Model details

MiniMax M2.5

MiniMax M2.5 is positioned within MiniMax's LLM family as a text-focused sibling to the newer M2.7 and M3 models, sharing the same generation lineage that anchors the company's productivity-oriented lineup. Its role is that of a workhorse text model rather than a flagship, aimed at teams that need predictable text generation, repository-scale question answering, and research-style summarization without stepping up to the most expensive tier. Third-party evaluators describe M2.5 as the practical default for text-heavy pipelines where cost per token matters more than cutting-edge reasoning, making it a natural fit for chatbots, knowledge assistants, and back-end processing jobs that need reliable throughput over a long context window.

In practical routing, M2.5 fills the role of a lower-cost MiniMax-family model for everyday text work, while the newer M3 is reserved for agentic coding, multimodal input, and very long context tasks. This split lets engineering teams run M2.5 as a steady default for repo Q&A, documentation search, and fallback paths, then escalate only the highest-value requests to M3. The combination supports a two-tier production strategy where M2.5 absorbs the bulk of routine language work and contributes to a balanced cost-and-capability architecture across the MiniMax text lineup.

MeganovaMiniMaxAI/MiniMax-M2.5minimax

Quick Info

Powered by
Provider
Meganova
Model key
MiniMaxAI/MiniMax-M2.5
Release date
Feb 12, 2026
Last updated
Feb 12, 2026
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$0.30
Output token cost
$1.20

Limits

Output tokens
131,072 tokens
Context window
204,800 tokens

Transparent token rates

Compare MiniMax M2.5 pricing

Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

Browse this family

Latest news about MiniMax M2.5

Merge Gateway

CoverageBenchmark

An InferenceX (SemiAnalysis) architecture profile covers MiniMax-M2.5 (and M2.7) as sparse MoE language models in MiniMax's M2 series, based on the technical report thesis that "mini activations can unleash maximum real-world intelligence." M2.5 is listed as released 2026-02-12 (matching MiniMax's announcement and Hugg The page documents specific architectural details: 62 MoE transformer layers, Grouped Query Attention with QK Norm, RoPE, Multi-Token Prediction (3 modules), Top-8/256 routing, RMSNorm, FP8 quantization, 197K context window, and d=3,072 token embeddings with a 200,064 vocabulary. It also cites M2.5's headline benchmark

Videos about MiniMax M2.5

More models around MiniMax M2.5