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Model: "gemma-4-12b"
not much happened today
mai-thinking-1 mai-image-2.5 mai-code-1-flash gemma-4-12b microsoft google vllm-project ollama llama-cpp model-training reinforcement-learning model-architecture multimodality model-deployment model-efficiency fine-tuning on-device-ai eliebakouch nrehiew_ mustafasuleyman minjiyoon90 lateinteraction harold_matmul googlegemma googleaidevs mtschannen armandjoulin osanseviero
Microsoft released the detailed technical report for MAI-Thinking-1, a generalist reasoning model trained without third-party distillation, achieving 97% on AIME 2025 and outperforming Sonnet 4.6 in human preference tests. The report was praised for transparency, revealing no synthetic data use, a unique scaling ladder recipe, and detailed training data composition including 50% code and 17.5% STEM. Microsoft also introduced Frontier Tuning for workflow-specific model adaptation, claiming efficiency gains up to 10× and GPT-5.4-level quality in Excel tasks, alongside new models like MAI-Image-2.5 and MAI-Code-1-Flash. Meanwhile, Google launched Gemma 4 12B, an Apache 2.0 multimodal model with an innovative encoder-free architecture designed for on-device use with 16GB VRAM, collapsing vision and audio encoders into the LLM backbone, receiving positive community feedback and immediate tooling support.