MiMo-V2.5-Pro vs o1-preview
MiMo-V2.5-Pro leads the LLM Stats Score 24.7 to 16.6. MiMo-V2.5-Pro is 48.3x cheaper per token.
Xiaomi · OpenAI · Updated for 2026
Which is better?
MiMo-V2.5-Pro leads the overall LLM Stats Score 24.7 to 16.6, ranking #160 overall.
The models split the 4 individual benchmarks reported for both models evenly.
On price, MiMo-V2.5-Pro is roughly 48.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiMo-V2.5-Pro 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-Pro
- overall performance matters — it scores 24.7 and ranks #160 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- cost matters — it's about 48.3x 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
- you need open weights you can self-host or fine-tune
Choose o1-preview
- you want predictable pricing at $15.00/M input and $60.00/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
31 reported for MiMo-V2.5-Pro · 8 for o1-preview
MiMo-V2.5-Pro outperforms in 2 benchmarks (MATH, SWE-Bench Verified), while o1-preview is better at 2 benchmarks (GPQA, MMLU).
Both models are evenly matched across the 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-Pro ($0.43/1M tokens) is 34.5x cheaper than o1-preview ($15.00/1M tokens).
For output processing, MiMo-V2.5-Pro ($0.87/1M tokens) is 69.0x cheaper than o1-preview ($60.00/1M tokens).
In conclusion, o1-preview is more expensive than MiMo-V2.5-Pro.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
MiMo-V2.5-Pro accepts 1,048,576 input tokens compared to o1-preview's 128,000 tokens. MiMo-V2.5-Pro can generate longer responses up to 131,072 tokens, while o1-preview is limited to 32,768 tokens.
License
Usage and distribution terms
MiMo-V2.5-Pro is licensed under MIT, while o1-preview uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
MiMo-V2.5-Pro was released on 2026-04-27, while o1-preview was released on 2024-09-12.
MiMo-V2.5-Pro is 20 months newer than o1-preview.
Apr 27, 2026
4 months ago
1.6yr newerSep 12, 2024
2.0 years 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-Pro is available from Xiaomi, DeepInfra, Novita. o1-preview is available from OpenAI, Azure.
MiMo-V2.5-Pro
o1-preview
Outputs Comparison
Judge for yourself.
Run your own prompts against MiMo-V2.5-Pro and o1-preview side-by-side, then vote on the output you prefer.
FAQ
Common questions about MiMo-V2.5-Pro vs o1-preview.