
Google has introduced the Gemini 3.8 Flash model, which is designed to perform more reasoning steps and call tools iteratively, potentially increasing token usage and costs for users. While the pricing remains the same as the previous version, the model's enhanced capabilities could lead to higher expenses. It has demonstrated superior performance in software engineering and autonomous AI tasks, surpassing competitors on several benchmarks. The model is available to consumers and developers, with a specialized version for governments and trusted partners through the Fairwind Program.
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This release quietly cements llama.cpp as the universal inference runtime by finally supporting NVIDIA's latest CUDA 13 stack alongside AMD's ROCm 10.0. The inclusion of native builds for Linux arm64 with Snapdragon chips, covering CPU, Adreno GPU, and Hexagon NPU, signals a serious push into mobile edge deployment. While Apple Silicon KleidiAI is disabled in this specific build, the broader hardware coverage means developers no longer need to compile from source for most modern accelerators. It’s less about new features and more about removing friction for anyone running local models on bleeding-edge or diverse hardware.
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Google DeepMind Launches Gemini Omni 1.1 Flash
10 developments
Google launched Gemini 4 Carbon, a new model variant aimed at providing high performance at a lower cost for inference tasks.