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The DeepSWE benchmark costs are per task, not per total run. Running models like Mimo V2.5 Pro can cost ~$225 for a full run, while Mimo V2.5 non-pro costs ~$7.15. Users should be aware of this before running expensive models.
MiMo 2.5 Pro has lowered its price to match DeepSeek V4 Pro, sparking a price war among AI model providers.
PilotWiMAE introduces a self-supervised framework that directly ingests noisy pilot observations for wireless channel representation learning, removing the unrealistic full-CSI assumption and enabling robust cross-frequency beam selection and channel estimation that beats supervised baselines.
According to the arena leaderboard, open weights models GLM and Mimo outperform Gemini 3.5 Flash in coding benchmarks.
This article tests four open-source Chinese AI models — Zhipu GLM 5.1, Moonshot Kimi K2.6, Stepfun MIMO 2.5 Pro, and DeepSeek V4 Pro — on programming tasks. It finds that GLM leads overall in most tasks but not absolutely; each model has its own strengths and weaknesses.
A pull request has been merged into llama.cpp to add support for the Mimo v2.5 model, enhancing the framework's compatibility with this specific AI architecture.
Mimo V 2.5 and Mimo V 2.5 Pro have been released, offering updated features and improvements.
Xiaomi released Mimo-V2.5, an open-weight AI model, adding to today’s string of open model drops alongside Qwen-27B.