
Together AI has unveiled a new architecture for model inference that combines endpoints, deployments, and configurations with a capacity-aware traffic split. This setup allows for advanced features like rollouts and A/B testing while maintaining zero-downtime updates. The platform uses immutable configurations to ensure consistent performance and easy rollback options. This approach simplifies the deployment process and enhances the reliability of AI applications by optimizing resource allocation and scaling.
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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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