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Model: "gelato-30b-a3b"
not much happened today
kimi-k2-thinking kimi-k3 gelato-30b-a3b omnilingual-wav2vec-2.0 moonshot-ai meta-ai-fair togethercompute qwen attention-mechanisms quantization fine-tuning model-optimization agentic-ai speech-recognition multilingual-models gui-manipulation image-editing dataset-release yuchenj_uw scaling01 code_star omarsar0 kimi_moonshot anas_awadalla akhaliq minchoi
Moonshot AI's Kimi K2 Thinking AMA revealed a hybrid attention stack using KDA + NoPE MLA outperforming full MLA + RoPE, with the Muon optimizer scaling to ~1T parameters and native INT4 QAT for cost-efficient inference. K2 Thinking ranks highly on LisanBench and LM Arena Text leaderboards, offering low-cost INT4 serving and strong performance in Math, Coding, and Creative Writing. It supports heavy agentic tool use with up to 300 tool requests per run and recommends using the official API for reliable long-trace inference. Meta AI released the Omnilingual ASR suite covering 1600+ languages including 500 underserved, plus a 7B wav2vec 2.0 model and ASR corpus. Additionally, the Gelato-30B-A3B model for computer grounding in GUI manipulation agents outperforms larger VLMs, targeting immediate agent gains. Qwen's image-edit LoRAs and light-restoration app were also highlighted.