Beam 1.0 vs MiMo-V2.6-Pro
MiMo-V2.6-Pro leads the LLM Stats Score 48.9 to 44.6. MiMo-V2.6-Pro is 1.1x cheaper per token.
Reflection AI · Xiaomi · Updated for 2026
Which is better?
MiMo-V2.6-Pro leads the overall LLM Stats Score 48.9 to 44.6, ranking #27 overall.
In the 2 individual benchmarks reported for both models, MiMo-V2.6-Pro wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, MiMo-V2.6-Pro is roughly 1.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Beam 1.0
- you want the most recent training data — it shipped Oct 2026
Choose MiMo-V2.6-Pro
- overall performance matters — it scores 48.9 and ranks #27 on LLM Stats
- your work emphasizes agents — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- cost matters — it's about 1.1x cheaper per token
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
22 reported for Beam 1.0 · 18 for MiMo-V2.6-Pro
Beam 1.0 outperforms in 0 benchmarks, while MiMo-V2.6-Pro is better at 2 benchmarks (DeepSWE 1.1, Terminal-Bench 2.1).
MiMo-V2.6-Pro significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Beam 1.0 ($0.40/1M tokens) is 1.1x cheaper than MiMo-V2.6-Pro ($0.43/1M tokens).
For output processing, Beam 1.0 ($1.20/1M tokens) is 1.4x more expensive than MiMo-V2.6-Pro ($0.87/1M tokens).
In conclusion, Beam 1.0 is more expensive than MiMo-V2.6-Pro.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
MiMo-V2.6-Pro has 518.7B more parameters than Beam 1.0, making it 103.5% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 1,048,576 tokens. Only Beam 1.0 specifies output context (131,072 tokens).
Input capabilities
Documented input modalities across available providers
MiMo-V2.6-Pro supports multimodal inputs, whereas Beam 1.0 does not.
MiMo-V2.6-Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.
Beam 1.0
MiMo-V2.6-Pro
License
Usage and distribution terms
Beam 1.0 is licensed under Apache 2.0, while MiMo-V2.6-Pro uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
MIT
Open weights
Release Timeline
When each model was launched
Beam 1.0 was released on 2026-10-16, while MiMo-V2.6-Pro was released on 2026-09-22.
Beam 1.0 is 1 month newer than MiMo-V2.6-Pro.
Oct 16, 2026
6 days ago
3w newerSep 22, 2026
1 months ago
Knowledge Cutoff
When training data ends
Beam 1.0 has a documented knowledge cutoff of 2026-06-30, while MiMo-V2.6-Pro's cutoff date is not specified.
We can confirm Beam 1.0's training data extends to 2026-06-30, but cannot make a direct comparison without MiMo-V2.6-Pro's cutoff date.
Jun 2026
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Provider Availability
Beam 1.0 is available from Together, Reflection AI. MiMo-V2.6-Pro is available from Xiaomi.
Beam 1.0
MiMo-V2.6-Pro
Outputs Comparison
Judge for yourself.
Run your own prompts against Beam 1.0 and MiMo-V2.6-Pro side-by-side, then vote on the output you prefer.
FAQ
Common questions about Beam 1.0 vs MiMo-V2.6-Pro.