Topic
Xiaomi
3 episodes
-
'Better than DeepSeek': Xiaomi's MiMo V2.6 Pro debuts as the top open weights model in the world alongside cheaper V2.6 Flash
Echo is skeptical that Xiaomi’s MiMo-V2.6-Pro really changes the open-weights frontier just because it tops one benchmark index, while Onyx argues the real story is the user-facing combo of open weights, low API pricing, million-token multimodal context, and a cheaper Flash tier that makes production adoption easier. They dig into whether the reinforcement-learning stack is genuinely novel or mostly expensive harness tuning, and land on Xiaomi as a serious systems company making open models more usable, not a magic leap in intelligence.
-
Open source Xiaomi MiMo V2.5 and V2.5 Pro are among the most efficient (and affordable) at agentic 'claw' tasks
Xiaomi's open-source MiMo-V2.5 and V2.5-Pro models claim top-tier efficiency for agentic 'claw' tasks—autonomous agents that handle email, content creation, and complex coding work. The Pro version uses 40-60% fewer tokens than GPT-5.4 or Claude Opus while costing a fraction as much. Cody questions whether token efficiency alone translates to real production wins, while Justy sees a genuine market opening for cost-conscious enterprises building agent workflows.
-
Xiaomi stuns with new MiMo V2 Pro LLM nearing GPT 5.2, Opus 4.6 performance at a fraction of the cost
Xiaomi's MiMo-V2-Pro LLM achieves near GPT-5.2 performance at 1/7th the cost through sparse architecture with only 42B active parameters out of 1T total, targeting autonomous agents over conversational AI