model releases

hexagon: Q6_K weight dequant speedup (#30121) hexagon: Q6_K weight dequant speedup Assisted-by: OpenCode unroll by another factor of 2 Assisted-by: OpenCode Website: https://llama.app Attestations: ht

hexagon: enable alloc_buffer_n (#30126) hex-bufs: add support for alloc_buffer_n hex-bufs: add support for splitting large tensors into separate buffers hex-bufs: update GGML_HEXAGON_MBUF to accept th

sycl: remove duplicate block-size defines from op headers (#29507) All were duplicates of the values in ggml/src/ggml-sycl/presets.hpp Website: https://llama.app Attestations: https://github.com/ggml-

sycl: add grouped MoE XMX GEMM (#29245) Co-authored-by: cwriter cwriter@localhost Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/53864714 macOS/iOS: macOS

sycl: fuse the delta-net alpha gate (add + unary + mul) (#29687) sycl: fuse the delta-net alpha gate (add + unary + mul) tests: cover the fused add + unary + mul chain sycl: give the fused alpha gate

CUDA: fix norm family kernels when ne[2]/ne[3] exceed grid dim limits (#28175) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/53919465 macOS/iOS: macOS App

cuda : Use byte strides for roll to allow non-contiguous ROLL operations (#29547) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/53926988 macOS/iOS: macOS

hex-mmadd: do not assume aligned read/write when bias-add is fused (#30133) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/53932639 macOS/iOS: macOS Apple

sycl: FWHT optimizations (#29605) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/53938516 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64

vendor : update cpp-httplib to 0.60.1 (#30134) Signed-off-by: Adrien Gallouët angt@huggingface.co Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/53949333 m

vulkan : fix TOP_K for +inf/NaN inputs and k = 1 on negative values (#30107) The bucket search in topk_nary_search.comp started from the range [0, 0xFF800000), which ends just below the ordered-uint m

llama: support MoE cache over multiple GPUs (#30112) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/53988921 macOS/iOS: macOS Apple Silicon (arm64) macOS A

CUDA: fix CCCL version guard breaking on major version rollover (#29453) CUDA: fix CCCL version guard breaking on major version rollover The guard compared the major and minor components independently

CUDA : looped PAD kernel for more than 65535 rows or slices (#30147) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/54006924 macOS/iOS: macOS Apple Silicon

CUDA: fix MMQ out-of-bounds reads (#29953) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/54029251 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silic

model : fix DFlash output head sharing (#30111) llama : fix DFlash output head sharing Assisted-by: Codex dflash : read tied output weights from GGUF metadata Assisted-by: Codex llama : share tied wor

CUDA: improve top-k algorithm selection (#28713) CUDA: radix top-k for large row counts Replaces CUB's per-row DeviceTopKKernel with a grid-over-rows radix select, gated on GGML_CUDA_TOPK_RADIX_MIN_RO

Musa FWHT fix (#30167) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/54083178 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, KleidiAI

arXiv:2610.10160v1 Announce Type: new Abstract: Mishandled checked baggage remains a recurrent issue in airport operations, and current recovery workflows still largely rely on tag-based tracking, whi

arXiv:2610.09464v1 Announce Type: new Abstract: Political discourse often uses rhetorical and persuasive language to frame narratives, influence public opinion, and mobilize audiences. While Bangla na

arXiv:2610.09026v1 Announce Type: cross Abstract: We present BEACON-SP, an ontology-grounded Graph Retrieval-Augmented Generation (GraphRAG) framework for clinician-facing decision support in behavior

arXiv:2610.10198v1 Announce Type: new Abstract: Behavior Foundation Models (BFMs) are emerging as a paradigm for translating human intentions into executable humanoid behaviors. As these models evolve

There are way too many forks to keep track of, so I've gotten lost. As far as I can tell, Radiance VLLM is best for models that fit in GPUs while some form of llama.cpp is probably best for MOE RAM-sp

I'm developing a benchmark for a low resource language and I don't want it to be leaked and used for training when it is being used to get predictions. For locally run models it shouldn't be a problem

arXiv:2610.10163v1 Announce Type: new Abstract: Linking people's appearance and actions to character identities is essential for understanding video narratives. We present a framework for identity-awa

arXiv:2603.13357v2 Announce Type: replace Abstract: Bi-CamoDiffusion is introduced, an evolution of the CamoDiffusion framework for camouflaged object detection. It integrates edge priors into early-s

Big new paper nobody is talking about ‼️ 🌎 Robot world models now have scaling laws. Meta trained an 8B-parameter JEPA on 15,000 hours of robot video to prove it. RoboJEPA (FAIR at Meta + Mila) imagin

arXiv:2610.09193v1 Announce Type: cross Abstract: MemoryAgentBench's Conflict Resolution split is read as measuring 'selective forgetting'. We execute the benchmark's own rule - the newest statement a

arXiv:2610.10383v1 Announce Type: new Abstract: Boosting converts weak hypotheses with a small edge over random guessing into highly accurate predictors, but the expressive power of the resulting clas

arXiv:2610.09804v1 Announce Type: new Abstract: Reinforcement learning is now central to eliciting reasoning in large language models, while in the popular algorithm Group Relative Policy Optimization

arXiv:2610.09467v1 Announce Type: cross Abstract: Contextual biasing supplies an ASR system with a list of expected words at inference time, but existing methods rely on word boundaries that Japanese

arXiv:2610.08815v1 Announce Type: new Abstract: Agentic AI-enabled automation cannot be safely deployed in high-stakes environments on probabilistic reasoning alone. A recurring risk is epistemic drif

arXiv:2610.09733v1 Announce Type: new Abstract: Multilingual LLMs answer the same multi-hop reasoning question across languages, but we lack a mechanistic account of whether they share an internal cir

arXiv:2610.10058v1 Announce Type: new Abstract: Repeated queries over shared documents incur redundant encoding, while caching model states introduces persistent storage costs. Building on CoMem's int

Opus5.5, Sol6.1, Fable, and Astra have all proven they can and the scene has exploded this past week. Part of that is from the tools and feedback loops maturing though. Are any open weight models (at

arXiv:2610.08917v1 Announce Type: new Abstract: While vision-language-action (VLA) models have advanced rapidly, running them at every control step remains expensive. Prior work accelerates VLA infere

arXiv:2610.10208v1 Announce Type: cross Abstract: Automatic audio scene description turns a recording into a text account of a situation. One difficulty is deciding which elements of the audio should

arXiv:2505.21468v2 Announce Type: replace Abstract: We present Causal Posterior Estimation (CPE), a novel method for Bayesian inference in simulator models, where evaluating the likelihood function is

arXiv:2610.09541v1 Announce Type: cross Abstract: Signals that predict whether a chain-of-thought (CoT) trace is correct are compared by AUC, but deploying one requires a threshold with a guarantee. W

arXiv:2610.09476v1 Announce Type: cross Abstract: Geometric and Spectral Alignment (GSA) characterizes trained networks through spectral concentration, physical-channel alignment, support structure, a

came across a pretty interesting technical breakdown of chatgpt's newly launched 'intelligent ui' feature, and thought this subreddit might find it interesting. for anyone unfamiliar with the concept,

arXiv:2610.09549v1 Announce Type: new Abstract: And-Inverter Graphs (AIGs) are fundamental representations for logic synthesis and verification in Electronic Design Automation (EDA). As structured rep

arXiv:2610.08862v1 Announce Type: cross Abstract: Household robots must accommodate new user instructions while executing ongoing tasks. Existing agents often regenerate or extensively revise the rema

arXiv:2610.09633v1 Announce Type: cross Abstract: The evaluation of coding agents generally strives to be as realistic as possible. In our study, we collect 4,782 agent sessions of real software engin

TL;DR: For my use case, mradermacher/Signal-3.8-27B-Terse-Coder.i1-Q4_K_M proved out. Ymmv based on your domain-specific tests. Time taken to solve problems compared to frontier models is massive; esp

arXiv:2610.10460v1 Announce Type: new Abstract: Multi-teacher on-policy distillation (MOPD) is used in two settings. In common-domain composition, several teachers score each student rollout from one