PyyanThe AI Index

Pyyan / Compare / MiMo-V2.6-Pro vs Qwen3.8-Flash-Next

MiMo-V2.6-Pro vs Qwen3.8-Flash-Next

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Open-Weight Models · verified 29 Sept 2026

XMiMo-V2.6-ProXiaomicurrent
Qwen3.8-Flash-NextAlibabacurrent
3 slots left
SpecificationMiMo-V2.6-ProQwen3.8-Flash-Next
SummaryA trillion parameters under the MIT licence.The most downloaded thing on Hugging Face right now, and a stated Qwen4 preview.
Context1M262K native, ~1M extended
Input ($/Mtok)Weights only$0.15
Output ($/Mtok)Weights only$0.47
LicenceMITOpen weights
Max outputNot published32K
Parameters1.02T total, 42B active125B total, 6B active
Released21 Sep 202626 Aug 2026
Model IDXiaomiMiMo/MiMo-V2.6-ProQwen/Qwen3.8-Flash-Next
CategoryOpen-Weight ModelsOpen-Weight Models
OfficialXiaomi ↗—

Highlighted rows are where these differ.

MiMo-V2.6-Pro

  • 1.02T total parameters, 42B active per token, a 4.1% activation ratio
  • Text, image, video and audio in, with a 1M token context
  • Shipped with 7,000+ reinforcement learning environments and the framework that trained it

Best for multimodal work on your own cluster.

Full spec sheet →

Qwen3.8-Flash-Next

  • 125B total parameters with only 6B active per token
  • Alibaba describes it as a preview of the Qwen4 architecture
  • Top of the Hugging Face trending list, with a GGUF build close behind it

Best for open weights at speed.

Full spec sheet →