MiMo V2.6 Flash vs Qwen3.8 Flash Next: Accuracy, Token Efficiency and Memory Use
Xiaomi’s MiMo V2.6 Flash is a large mixture-of-experts (MoE) model with 309 billion parameters, of which 15 billion are activated per token.
Proof1 independent outlet
Key points
- Xiaomi initially released an “RL” version, followed by MiMo-V2.6-Flash-MOPD, which uses multi-teacher on-policy distillation to reduce repetitive tool calls, a behavior that can consume substantial resources without bringing an agent any closer to completing its task.
- But I wanted to know how it compares to Qwen3.8 Flash Next in practice.
- To investigate, I compare Qwen3.8 Flash Next at xhigh reasoning effort with MiMo-V2.6-Flash-MOPD with thinking enabled.
- Qwen3.8 Flash Next vs MiMo V2.6: Accuracy and Token Efficiency
Sources (1)
- [1]MiMo V2.6 Flash vs Qwen3.8 Flash Next: Accuracy, Token Efficiency and Memory UseThe Kaitchup (Benjamin Marie) · Oct 16, 02:50 AM
Xiaomi’s MiMo V2.6 Flash is a large mixture-of-experts (MoE) model with 309 billion parameters, of which 15 billion are activated per token.
Xiaomi initially released an “RL” version, followed by MiMo-V2.6-Flash-MOPD, which uses multi-teacher on-policy distillation to reduce repetitive tool calls, a behavior that can consume substantial resources without bringing an agent any closer to completing its task.
Extractive summary: sentences quoted from the sources.
Hype check
Independently evaluated6 independent looks since
- Evaluation · Oct 16, 2026Competence-Based Evaluation of Logical Reasoning in Large Language Models
- Evaluation · Oct 16, 2026BlenderWorld Benchmark from Alibaba
- Evaluation · Oct 16, 2026Qwen Flash Next potential SOTA Q2 nobody talks about
- Evaluation · Oct 16, 2026The actual state of open-weight models vs. frontier models
- Evaluation · Oct 16, 2026FLUX 3 vs KREA 2 vs Z image turbo vs Qwen 2.1
- Evaluation · Oct 16, 2026PresenceBench: An Exploratory Evaluation of Large Language Model Adaptation to User State
Before this
- Oct 16, 2026Welcome Beam: a 501B open model you can own, customize, and scale
- Oct 15, 2026capy-flash: Qwen3.8-Flash-Next (125B MoE) in full NVFP4 on two 16 GB consumer GPUs
- Oct 15, 2026huggingface/transformers v5.20.0: Release v5.20.0
- Oct 15, 2026Local and Distributed Large LLM Inference with MLX and RDMA on Mac Studio
- Oct 15, 2026Learning to Think and Explore in 3D World
- Oct 14, 2026Mapping the Post-Transformer Architecture Landscape in 2026 [D]
