
Google has launched Gemini 3.5 Transcribe, a new AI transcription model that improves on its predecessor, Chirp 3, by supporting over 85 languages and automatically removing filler words. The model allows users to customize vocabulary for specialized jargon and can attribute speech to up to three speakers. While the release of the Gemini 3.5 Pro model is still awaited, 3.5 Transcribe is now available for macOS users and developers. This update enhances transcription accuracy and usability, making it a valuable tool for those needing precise audio-to-text conversion.
Read originalThe v0.28.0 release of vLLM introduces substantial improvements in performance and functionality, particularly for the Kimi-K3 model. With the addition of Decode Context Parallel support and fused FlashKDA decode kernels, the update significantly enhances processing speed and efficiency. DeepSeek V4 now includes sparse MLA support and advances in speculative decoding, offering better execution on both NVIDIA and AMD hardware. These updates make vLLM more robust and adaptable, providing developers with enhanced tools for deploying and executing models on a broader range of hardware configurations.
The b10657 release of llama.cpp brings new OpenCL binary kernels, enhancing performance and compatibility across a wide range of systems. This update includes specific improvements for Apple Silicon, with KleidiAI support, and Vulkan on Ubuntu, making it more accessible for developers using these platforms. While no new model architectures are introduced, the release focuses on strengthening llama.cpp's capabilities as an inference runtime, particularly for those not using NVIDIA hardware. With ROCm 7.14 support on Ubuntu and CUDA 12 and 13 DLLs for Windows, llama.cpp continues to evolve as a versatile tool for AI model deployment. This release underscores the commitment to broadening hardware compatibility and optimizing performance across different environments.