The Oct 8 2026 release adds new fast‑Fourier‑Hadamard kernels that handle widths from 1,024 to 8,192 on NVIDIA GPUs.
NoteBy OossaPublished by Oossa: 1 min read
The llama.cpp project released version b11482 on Oct 8 2026. It adds CUDA FWHT kernels that work for block widths above 512, extending support to 1,024‑8,192 for both FP32 and FP16 data. The change reuses the existing F16 infrastructure and passes tests on an A10 GPU. Existing warp‑width kernels (64‑512) remain unchanged.
GPU users can now run larger‑width matrix multiplications faster with llama.cpp.
Models
The company’s new three‑agent Claude‑based reviewer found 73.43% of core‑claim errors, far above the previous best of 14.81%.
Models
Mistral's new trillion‑parameter model scores 38 on an independent index, but costs more per task than competing open models.
Models
OpenAI reported two influence campaigns that used AI‑generated content to plant false stories in real media and blocked the involved accounts.
Oossa · Newsletter
The week in AI, explained
Every Monday: the stories worth knowing, in plain language. Free, no spam.
