Gemini 1.5 Pro vs MiMo-V2.6-Pro
MiMo-V2.6-Pro leads the LLM Stats Score 49.8 to 12.0. MiMo-V2.6-Pro is 8.0x cheaper per token.
Google · Xiaomi · Updated for 2026
Which is better?
MiMo-V2.6-Pro leads the overall LLM Stats Score 49.8 to 12.0, ranking #19 overall.
On price, MiMo-V2.6-Pro is roughly 8.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 1.5 Pro also accepts a larger context window (2,097,152 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 Gemini 1.5 Pro
- you process long inputs — it offers a 2,097,152 token context window
Choose MiMo-V2.6-Pro
- overall performance matters — it scores 49.8 and ranks #19 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- cost matters — it's about 8.0x cheaper per token
- you want the most recent training data — it shipped Sep 2026
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Individual benchmarks
23 reported for Gemini 1.5 Pro · 18 for MiMo-V2.6-Pro
Gemini 1.5 Pro and MiMo-V2.6-Prodon'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, Gemini 1.5 Pro ($2.50/1M tokens) is 5.7x more expensive than MiMo-V2.6-Pro ($0.43/1M tokens).
For output processing, Gemini 1.5 Pro ($10.00/1M tokens) is 11.5x more expensive than MiMo-V2.6-Pro ($0.87/1M tokens).
In conclusion, Gemini 1.5 Pro is more expensive than MiMo-V2.6-Pro.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Gemini 1.5 Pro accepts 2,097,152 input tokens compared to MiMo-V2.6-Pro's 1,048,576 tokens. Only Gemini 1.5 Pro specifies output context (8,192 tokens).
Input capabilities
Documented input modalities across available providers
Both Gemini 1.5 Pro and MiMo-V2.6-Pro support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemini 1.5 Pro
MiMo-V2.6-Pro
License
Usage and distribution terms
Gemini 1.5 Pro is licensed under a proprietary license, while MiMo-V2.6-Pro uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
MIT
Open weights
Release Timeline
When each model was launched
Gemini 1.5 Pro was released on 2024-05-01, while MiMo-V2.6-Pro was released on 2026-09-22.
MiMo-V2.6-Pro is 29 months newer than Gemini 1.5 Pro.
May 1, 2024
2.4 years ago
Sep 22, 2026
-1 days ago
2.4yr newerKnowledge Cutoff
When training data ends
Gemini 1.5 Pro has a documented knowledge cutoff of 2023-11-01, while MiMo-V2.6-Pro's cutoff date is not specified.
We can confirm Gemini 1.5 Pro's training data extends to 2023-11-01, but cannot make a direct comparison without MiMo-V2.6-Pro's cutoff date.
Nov 2023
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Provider Availability
Gemini 1.5 Pro is available from Google. MiMo-V2.6-Pro is available from Xiaomi.
Gemini 1.5 Pro
MiMo-V2.6-Pro
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemini 1.5 Pro and MiMo-V2.6-Pro side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemini 1.5 Pro vs MiMo-V2.6-Pro.