MiMo-V2.5 vs MiniMax M2.7
MiMo-V2.5 and MiniMax M2.7 are closely matched at 35.5 and 35.5 on the LLM Stats Score. MiMo-V2.5 is 2.5x cheaper per token.
Xiaomi · MiniMax · Updated for 2026
Which is better?
MiMo-V2.5 and MiniMax M2.7 are closely matched on the overall LLM Stats Score at 35.5 and 35.5.
In the 3 individual benchmarks reported for both models, MiMo-V2.5 wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, MiMo-V2.5 is roughly 2.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiMo-V2.5 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose MiMo-V2.5
- you value its reported benchmark strengths — it wins 2 of 3 exact shared results
- cost matters — it's about 2.5x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Apr 2026
Choose MiniMax M2.7
- you want predictable pricing at $0.30/M input and $1.20/M output
At a glance
The differences that matter most.
Individual benchmarks
14 reported for MiMo-V2.5 · 11 for MiniMax M2.7
MiMo-V2.5 outperforms in 2 benchmarks (Finance Agent v2, Terminal-Bench 2.0), while MiniMax M2.7 is better at 1 benchmark (SWE-Bench Pro).
MiMo-V2.5 shows notably better performance in the majority of benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, MiMo-V2.5 ($0.17/1M tokens) is 1.8x cheaper than MiniMax M2.7 ($0.30/1M tokens).
For output processing, MiMo-V2.5 ($0.34/1M tokens) is 3.6x cheaper than MiniMax M2.7 ($1.20/1M tokens).
In conclusion, MiniMax M2.7 is more expensive than MiMo-V2.5.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
MiMo-V2.5 accepts 1,048,576 input tokens compared to MiniMax M2.7's 196,608 tokens. MiniMax M2.7 can generate longer responses up to 196,608 tokens, while MiMo-V2.5 is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
MiMo-V2.5 supports multimodal inputs, whereas MiniMax M2.7 does not.
MiMo-V2.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.
MiMo-V2.5
MiniMax M2.7
License
Usage and distribution terms
Both models are licensed under MIT.
Both models share the same licensing terms, providing consistent usage rights.
MIT
Open weights
MIT
Open weights
Release Timeline
When each model was launched
MiMo-V2.5 was released on 2026-04-22, while MiniMax M2.7 was released on 2026-03-18.
MiMo-V2.5 is 1 month newer than MiniMax M2.7.
Apr 22, 2026
5 months ago
1mo newerMar 18, 2026
6 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
MiMo-V2.5 is available from Novita, DeepInfra. MiniMax M2.7 is available from Fireworks, MiniMax, Novita, DeepInfra.
MiMo-V2.5
MiniMax M2.7
Outputs Comparison
Judge for yourself.
Run your own prompts against MiMo-V2.5 and MiniMax M2.7 side-by-side, then vote on the output you prefer.
FAQ
Common questions about MiMo-V2.5 vs MiniMax M2.7.