AI model
The cheaper tier of Xiaomi's MiMo-V2.6 family, sharing the family's million-token context and multimodal input at roughly a third of Pro's token price.
Xiaomi's $850,000 and $2.62 million cover 30 reinforcement-learning steps apiece on models it had already pretrained. Xiaomi published the environments and the RL code but not the 7,000-plus task datasets behind them.
Perspective Coverage
7 publishersReality
Artificial Analysis measured the score itself, and the weights are on Hugging Face under MIT, but MiMo-V2.6-Pro holds 1.02 trillion parameters, so most teams will reach it through an API at $0.43 per million input tokens.
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Two agentic post-training jobs, a 1.02-trillion-parameter model and a 309-billion cousin, ran with step time, reward and infrastructure error rates on the open web. Both stopped near step 30, and both models are still unreleased.
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Sol lists at $2 and $10 per million tokens and Luna at $0.10 and $0.50. The per-task savings OpenAI published come mostly from the lower price, and the cheaper tier scores below its predecessor on computer use.
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Artificial Analysis scores the new Xiaomi model first among open weights and twelve points behind Claude Opus 5.5, and the cheaper Flash tier is the one an operator should put in front of a real queue.
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