
Google DeepMind has introduced the Gemini 3.6 Flash series, which includes the 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber models. The 3.6 Flash model improves token efficiency by 17% and reduces costs, enhancing coding and knowledge work. The 3.5 Flash-Lite model is optimized for high throughput tasks, offering 350 output tokens per second. Meanwhile, the 3.5 Flash Cyber model is tailored for cybersecurity, detecting and fixing vulnerabilities efficiently. These models are now available for developers and enterprises, promising advancements in AI agent performance and cybersecurity.
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This release quietly expands llama.cpp's hardware support to include Qualcomm's Hexagon NPU on Linux arm64, a significant step for local inference on Snapdragon devices. It also updates CUDA builds to version 13.4 and introduces ROCm 10.0 binaries, keeping the project aligned with the latest NVIDIA and AMD driver ecosystems. KleidiAI on Apple Silicon is temporarily disabled in this build, likely due to stability checks rather than a feature rollback. For developers targeting edge AI or diverse GPU stacks, this update ensures broader compatibility without requiring custom compilation.
© Lev SelectorNVIDIA introduced the NVFP4 4-bit format and SoL-Pi technology, which uses 2x fewer tokens for improved efficiency.
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Google DeepMind Unveils Gemini 3.5 Flash Cyber
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