Berth is a Go-based GPU resource manager for CUDA workloads

tandem.cpp, a llama.cpp patch set, runs Qwen3.8-Flash-Next at 97 tok/s on an RTX 4090 with 64 GB DDR4, claimed 3.3× faster than llama.cpp. It keeps hot experts on the GPU and offloads the rest to CPU, targeting single-user decode for any MoE model llama.cpp supports.

Chatbots like Claude, ChatGPT and Gemini blend traditional googling with training-data recall, which works for simple look-ups like the Empire State Building's height but can pick the wrong source for obscure queries. Wired notes Google is pushing AI Mode in its own search engine.

A r/LocalLLaMA post proposes that community members build their own private quality benchmarks, especially to compare models across quantization levels, rather than fixating on tokens-per-second throughput.

After an October ICO report said foundation-model training processes personal data, Meta, OpenAI and Apple all offer UK users opt-out routes. Meta asks third-party objectors to supply the prompt and a screenshot of the output; the ICO says technical means of checking whether a person's data sits in a trained model are currently limited.