MiMo-V2.6-Flash vs o1
MiMo-V2.6-Flash leads the LLM Stats Score 45.6 to 20.9. MiMo-V2.6-Flash is 150.0x cheaper per token.
Xiaomi · OpenAI · Updated for 2026
Which is better?
MiMo-V2.6-Flash leads the overall LLM Stats Score 45.6 to 20.9, ranking #29 overall.
On price, MiMo-V2.6-Flash is roughly 150.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiMo-V2.6-Flash 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-V2.6-Flash
- overall performance matters — it scores 45.6 and ranks #29 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- cost matters — it's about 150.0x 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 Sep 2026
- you need open weights you can self-host or fine-tune
Choose o1
- 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
16 reported for MiMo-V2.6-Flash · 19 for o1
MiMo-V2.6-Flash and o1don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, MiMo-V2.6-Flash ($0.14/1M tokens) is 107.1x cheaper than o1 ($15.00/1M tokens).
For output processing, MiMo-V2.6-Flash ($0.28/1M tokens) is 214.3x cheaper than o1 ($60.00/1M tokens).
In conclusion, o1 is more expensive than MiMo-V2.6-Flash.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
MiMo-V2.6-Flash accepts 1,048,576 input tokens compared to o1's 200,000 tokens. Only o1 specifies output context (100,000 tokens).
Input capabilities
Documented input modalities across available providers
MiMo-V2.6-Flash supports multimodal inputs, whereas o1 does not.
MiMo-V2.6-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
MiMo-V2.6-Flash
o1
License
Usage and distribution terms
MiMo-V2.6-Flash is licensed under MIT, while o1 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-V2.6-Flash was released on 2026-09-22, while o1 was released on 2024-12-17.
MiMo-V2.6-Flash is 21 months newer than o1.
Sep 22, 2026
0 days ago
1.8yr newerDec 17, 2024
1.8 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-V2.6-Flash is available from Xiaomi. o1 is available from Azure, OpenAI.
MiMo-V2.6-Flash
o1
Outputs Comparison
Judge for yourself.
Run your own prompts against MiMo-V2.6-Flash and o1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about MiMo-V2.6-Flash vs o1.