AI model
Xiaomi's flagship MiMo model, a sparse mixture-of-experts system with multimodal input and a million-token context, published as open weights.
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.
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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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US companies are buying the cheapest AI model that can finish a job, the FT reports, with Ramp data pointing to a 41% fall in effective token prices. Investors now have to value AI vendors on cost per completed task, a figure that shifts with the workload.
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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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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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