github

<details open> jinja : fix quadratic cost in gather_string_parts (#27034) * jinja : fix quadratic cost in gather_string_parts * fix some comments * remove test </details> **Website:** - <https://llama.app> **macOS/iOS:** - [macOS Apple Silicon (arm64)](https://github.com/g

<details open> chat : pass reasoning_effort to template * chat: add reasoning_effort to common_chat_templates_inputs Store OpenAI Chat Completions reasoning_effort and make it available to jinja templates (with model specific translations where required). Assisted-by: llama.c

<details open> sync : ggml </details> **Website:** - <https://llama.app> **macOS/iOS:** - [macOS Apple Silicon (arm64)](https://github.com/ggml-org/llama.cpp/releases/download/b10433/llama-b10433-bin-macos-arm64.tar.gz) - macOS Apple Silicon (arm64, KleidiAI enabled) [DISABLE

<details open> ggml : recurrent state rollback for ggml_ssm_scan (#26623) * Initial changes for Recurrent state rollback for nemotron for cpu and cuda * Removing CPU RS rollback. Will enable it in subsequent PRs * addition of test case * Removing assert and calling runtime A

<details open> llama : allow virtual igpu devices (#26953) * llama : allow virtual igpu devices * cont : better comment </details> **Website:** - <https://llama.app> **macOS/iOS:** - [macOS Apple Silicon (arm64)](https://github.com/ggml-org/llama.cpp/releases/download/b1043

<details open> server: allow accessing /metrics and /slots during llama_decode() (#27041) * server_queue::worker * call llama_decode inside yield_to_queue * also handle process_mtmd_chunk * clean up * nits * rm test </details> **Website:** - <https://llama.app> **macOS/

<details open> tests : replace personal home directory paths with generic placeholders (#27043) Scrub developer-specific /home/<user>/ paths from example docs and test fixtures so they don't leak into the tree. - examples/test-cmake/README.md: /home/danbev/... -> /path/to/llam

<details open> sycl: fuse mul_mat(gate) + mul_mat(up) + GLU for q4_K dense FFN (#26779) Measured on Arc Pro B70 (Battlemage, Level Zero), llama-bench -r 20, two interleaved rounds, tg128: qwen2.5-3B-Instruct Q4_K_M 154.18 -> 158.53 t/s +2.8% gemma-2-2b-it Q4_K_M

<details open> sycl: fuse the gated-delta-net state writeback cpy (#26643) Port of https://github.com/ggml-org/llama.cpp/pull/23940. Arc Pro B70, Qwen 3.6 27B Q4_K - Medium (48 of its 64 blocks run gated_delta_net), -ngl 99 -fa 1 -ctk f16 -ctv f16 -b 2048 -ub 2048, interleaved

<details open> dflash : clarify output logging of target_layer_ids (#27013) This commit tries to make the logging of target_layer_ids a bit clearer and easier to read. Currently the output generated looks like this: ```console 0.00.468.624 D load_arch_hparams: DFlash extract_l