2026-10-29

[SYCL] add DPAS flash attention kernel for quantized KV cache ( #31125 ) sycl : add DPAS flash attention kernel for quantized KV cache Decode and small batches (1 to 31 query tokens) now run flash attention straight on q4_0 and q8_0 KV blocks, instead of scalar dequant or converting the whole cache to f16 per call. Q.K uses s8 x s4 and s8 x s8 DPAS on XMX, V.P stays f16. dpas.s4.s8 is inline vISA since joint_matrix has no s4. Covers head sizes 64 to 512, GQA up to 32 and attention sinks. Prompts stay on the existing kernels. GGML_SYCL_FA_DPAS=0 turns it off. B580, Llama 3.1 8B Q4_K_M, q4_0 KV, tg128: 31.3 to 54.2 t/s at 16K context. FLASH_ATTN_EXT 4582/4584, same 2 failures as master. Assisted-by: Claude sycl : 192 head dropped, Wildcat Lake added to docs Assisted-by: Claude sycl : stricter checks from review Assisted-by: Claude [SYCL] : rename XMX macro, add GGML_SYCL_SUPPORT_XMX option, document DPAS Assisted-by: Claude Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/61175196 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, KleidiAI enabled) DISABLED macOS Intel (x64) iOS XCFramework Linux: Ubuntu x64 (CPU) Ubuntu arm64 (CPU) Ubuntu s390x (CPU) Ubuntu 26.04 s390x (CPU) Ubuntu 26.04 s390x (zDNN) Ubuntu x64 (Vulkan) Ubuntu arm64 (Vulkan) Ubuntu x64 (CUDA 12) - CUDA 12.8 libraries Ubuntu x64 (CUDA 13) - CUDA 13.4 libraries Ubuntu arm64 (CUDA 13) - CUDA 13.4 libraries Ubuntu x64 (ROCm 10.0) Ubuntu x64 (OpenVINO) Ubuntu x64 (SYCL FP32) Ubuntu x64 (SYCL FP16) Linux arm64 (Snapdragon: CPU, Adreno GPU, Hexagon NPU) - setup guide Android: Android arm64 (CPU) Android arm64 (Snapdragon: CPU, Adreno GPU, Hexagon NPU) - setup guide Windows: Windows x64 (CPU) Windows arm64 (CPU) Windows arm64 (OpenCL Adreno) Windows x64 (CUDA 12) - CUDA 12.4 DLLs Windows x64 (CUDA 13) - CUDA 13.4 DLLs Windows arm64 (CUDA 13) - CUDA 13.4 DLLs Windows x64 (Vulkan) Windows arm64 (Vulkan) Windows x64 (OpenVINO) Windows x64 (SYCL) Windows x64 (ROCm 10.0) openEuler: DISABLED openEuler x86 (310p) openEuler x86 (910b, ACL Graph) openEuler aarch64 (310p) openEuler aarch64 (910b, ACL Graph) UI: UI

benchmarked GPU Unlock on my 3090 in ComfyUI. It's a Linux kernel module that lifts the GeForce FP16/BF16 tensor-core throttle on RTX 30 cards. ComfyUI Stock Unlock Unlock + undervolt Z-Image Turbo BF16, 1024², 8 steps 7.46 s/img 4.95 (+51%) 4.82 (+55%) SD 1.5 FP16, 1024², 30 steps 6.40 s/img 4.64 (+38%) 4.52 (+41%) Same images: every output's pixels were SHA-256 identical to stock at a fixed seed, including a 2-hour soak of 540 batches. Energy per image down 40% (2,369 J → 1,410 J). The weird part: my undervolt slowed the card at stock but sped it up once unlocked, because the card then hits its power limit and lower voltage buys clocks. Don't use --fast in ComfyUI if you want the gain. It switches matmuls to FP16 accumulation, which isn't throttled to begin with. Linux only. Only a full power-off reverts it. Github repo: https://github.com/Esequiel378/gpu-unlock-3090-results submitted by /u/esequiel378 to r/StableDiffusion [link] [comments]

sycl : vectorize reordered-layout dequantization stores (Q4_0, K-quants, IQ3, MXFP4) ( #30976 ) sycl : widen reordered q4_0 dequantization stores The reordered-layout Q4_0 conversion kernel processed one qs byte per work-item with two scalar stores, strided 16 elements apart. Give it the same treatment the Q8_0 kernel got in #30775 : a flat sycl::range<1> launch with four qs bytes (8 outputs) per work-item inside one 32-element block and two vec<dst_t,4> stores. Same float math and rounding as the scalar kernel; output is bit-identical. The existing k % QK4_0 == 0 assert guarantees whole 32-element blocks, so the k/8 launch covers every row exactly. The now-unreferenced scalar reorder kernel is removed. Arc Pro B70, primed prefill (prefill after decode on a reorder-installed tensor): +6.4% to +7.3% pp512/pp2048 on Q4_0 models (tested up to 27B dense); fresh-layout prefill and decode unchanged; PPL within run noise. sycl : vectorize reordered q4_K dequantization stores The reordered-layout Q4_K conversion kernel already loads its quantized inputs through sycl::vec but writes the dequantized results with scalar stores. Build the results in a vec<dst_t,n> register and emit two vector stores instead. Same per-element math; output is bit-identical. Arc Pro B70, primed prefill (prefill after decode on a reorder-installed tensor): +14.7% to +15.3% pp512/pp2048 on Q4_K-dominant models (tested up to 27B dense); fresh-layout prefill, decode and PPL unchanged. sycl : remap reordered q5_K dequantization to vec4 loads/stores The reordered-layout Q5_K conversion kernel gave each thread only four outputs fed by scalar ql/qh byte loads plus a local-memory scale broadcast, so the stores were never its bottleneck: widening the stores alone measured within noise on mixed-quant models and +0.5% on a q5_K-dominant model. Re-decompose to 32 threads per block, each consuming four consecutive ql and qh bytes and emitting two aligned vec<dst_t,4> stores; a 4-element run shares one scale pair, so the per-element math and the output are identical. Arc Pro B70, primed prefill on a q5_K-dominant 27B model: +3.6% pp512/pp2048 over the scalar kernel; fresh-layout prefill, decode and PPL unchanged. The GET_ROWS reorder path moves to the same 32-thread decomposition. sycl : remap reordered q6_K dequantization to vec4 stores The reordered-layout Q6_K conversion kernel wrote four scalars per thread, strided 32 elements apart, each pair of neighbors sharing neither instruction stream nor store transaction. Re-decompose the same 64-thread work-group so each thread emits one aligned vec<dst_t,4>: a 4-element run shares one 16-element scale group, one ql nibble source and one qh bit pair, so the per-element math and the output are identical to the scalar kernel. Arc Pro B70, primed prefill: +28.7% pp512/pp2048 on a Q6_K 27B model; fresh-layout prefill, decode and PPL unchanged. sycl : vectorize reordered q3_K dequantization stores Each thread of the reordered-layout Q3_K conversion kernel already computes four consecutive outputs; build them in a vec<dst_t,4> register and emit one vector store instead of four scalars. Same per-element math; output is bit-identical. Arc Pro B70, primed prefill: +16.8% pp512/pp2048 on a Q3_K-dominant 27B model; fresh-layout prefill, decode and PPL unchanged. sycl : vectorize reordered iq3_xxs/iq3_s dequantization stores Both reordered-layout IQ3 conversion kernels write eight contiguous outputs per thread as scalar stores (four from each grid lookup). Build two vec<dst_t,4> registers and emit two vector stores. Same per-element math; output is bit-identical. Arc Pro B70, primed prefill: +20.3% to +21.1% pp512/pp2048 on IQ3_XXS- and IQ3_S-dominant 27B models; fresh-layout prefill, decode and PPL unchanged. sycl : remap reordered q2_K dequantization to vec4 stores Re-decompose the reordered-layout Q2_K conversion kernel the same way as Q6_K: one aligned vec<dst_t,4> per thread instead of four scalars strided 32 apart. A 4-element run shares one scale byte and one 2-bit lane, so the per-element math and the output are identical to the scalar kernel. Arc Pro B70, primed prefill: +13.1% pp512/pp2048 on a Q2_K-dominant 27B model; fresh-layout prefill, decode and PPL unchanged. sycl : widen reordered mxfp4 dequantization stores Give the reordered-layout MXFP4 conversion kernel the same flat sycl::range<1> launch as Q4_0: four qs bytes (8 outputs) per work-item inside one 32-element block and two vec<dst_t,4> stores. Same LUT lookups and per-block scale; output is bit-identical. The k % QK_MXFP4 == 0 assert guarantees whole blocks, so the k/8 launch covers every row exactly. The old scalar kernel is removed. The reordered layout for MXFP4 is installed on the MoE expert path (reorder_qw_mxfp4_moe); dense MXFP4 tensors keep the normal layout. Arc Pro B70, MXFP4 MoE 20B model: +57% pp2048 / +61% pp512 prefill (primed and fresh alike), decode unchanged, PPL within the model's run-to-run noise. Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/61167328 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, KleidiAI enabled) DISABLED macOS Intel (x64) iOS XCFramework Linux: Ubuntu x64 (CPU) Ubuntu arm64 (CPU) Ubuntu s390x (CPU) Ubuntu 26.04 s390x (CPU) Ubuntu 26.04 s390x (zDNN) Ubuntu x64 (Vulkan) Ubuntu arm64 (Vulkan) Ubuntu x64 (CUDA 12) - CUDA 12.8 libraries Ubuntu x64 (CUDA 13) - CUDA 13.4 libraries Ubuntu arm64 (CUDA 13) - CUDA 13.4 libraries Ubuntu x64 (ROCm 10.0) Ubuntu x64 (OpenVINO) Ubuntu x64 (SYCL FP32) Ubuntu x64 (SYCL FP16) Linux arm64 (Snapdragon: CPU, Adreno GPU, Hexagon NPU) - setup guide Android: Android arm64 (CPU) Android arm64 (Snapdragon: CPU, Adreno GPU, Hexagon NPU) - setup guide Windows: Windows x64 (CPU) Windows arm64 (CPU) Windows arm64 (OpenCL Adreno) Windows x64 (CUDA 12) - CUDA 12.4 DLLs Windows x64 (CUDA 13) - CUDA 13.4 DLLs Windows arm64 (CUDA 13) - CUDA 13.4 DLLs Windows x64 (Vulkan) Windows arm64 (Vulkan) Windows x64 (OpenVINO) Windows x64 (SYCL) Windows x64 (ROCm 10.0) openEuler: DISABLED openEuler x86 (310p) openEuler x86 (910b, ACL Graph) openEuler aarch64 (310p) openEuler aarch64 (910b, ACL Graph) UI: UI

I'm a visual person (not sure that's actually a thing, but it's how I'd describe myself). Before I build anything, I need to see it first: how the services talk, what happens on a failed payment, where the state changes. So the design stage always comes first for me, with sequence diagrams, activity flows, state machines and the odd C4, and only then do I start writing code. These days I do that design work with Claude, from the CLI. Finished diagrams end up in my Obsidian vault, which I browse from the terminal with emeraldian , a TUI for Obsidian I also built. Getting them to finished is the fiddly bit, though. Claude Code writes lovely mermaid. It just can't show it to you. Every tweak meant copying the source into a viewer in another app, having a look, coming back, asking for a change, round again. Hard to iterate on a design you can't see. So I made merman, a Claude Code mod that renders mermaid live, right in the terminal. Ask for a sequence diagram and the actual diagram appears in the reply. Move an arrow and it redraws. Flowcharts, sequence, state, class and ER diagrams all work, as do bar, line and pie charts and gantt. Tables come out properly coloured too. As for the name, it felt only right. Who better to show off a mermaid than a merman? - A full reply renders in about 2 ms, so no lag - 16 colour themes, `/merman theme nord` to switch - About 355 tokens once per conversation (a small hint so Claude knows it can draw), or nothing if you switch that off - Claude Code's own UI is left alone, it only touches the replies It installs as a Claude Code plugin, one line (needs 2.1.311+): claude plugin marketplace add iamrohithrnair/merman && claude plugin install merman@merman Then /reload-plugins and /merman demo to see everything it draws. https://github.com/iamrohithrnair/merman (MIT) Note: C4 isn't supported yet, it stays as source for now. If you lean on C4 too, shout and I'll bump it up the list. Same for any diagram that comes out wonky. Send me the markdown and I'll have a look. It started as a fork of prismantis, and Claude Code made most of the changes since, with me steering and checking every render. The focus was keeping it lean on speed, memory and tokens. If you find this useful, a ⭐ on the repo would be much appreciated. It helps others discover it too. Thanks for the support! submitted by /u/100xbuilder to r/ClaudeAI [link] [comments]

submitted by /u/Boomfrag to r/LocalLLaMA [link] [comments]

Carl Franzen / VentureBeat : Google is rolling out Gemini 4 Carbon to selected cybersecurity defenders through Fairwind at $2/1M input and $10/1M output tokens, rising to $4 and $20 later — Google announced its latest and most intelligent frontier AI model today: Gemini 4 Carbon promises improvements in cybersecurity …

Overview This release adds the LiquidAI LFM3 family (text, vision, audio and omni) together with a new experimental streaming-audio API in mtmd , and wires realtime audio in and out of the server through the new /v1/realtime and /tts endpoints. A batch of new architectures landed: DeepSeek V4.1 Flash, SenseNova U1, Beam, Kolibri-1, Flint, Muse Spark, Granite Switch Decision, plus decision/embedding models from LiquidAI, Baidu and NVIDIA. The core got sparse-attention (QSA/DSA) reworked onto a fused masking op, a 50/50 SLRU cache for host-resident MoE experts, and cleaner no_alloc memory handling; the server got router memory-management and tool-calling improvements; the UI can now browse and download models straight from HF Hub, search conversations and compact them. Finally, ggml was bumped to v0.28.0, bringing GGML_OP_TOP_K_MASK , -1 expert-index semantics and large backend performance work (CUDA chunked graph launches, SYCL graph replay, OpenCL Q2_K/Q3_K, Hexagon HTP rework, KleidiAI SVE kernels). Highlights LFM3 family: LFM3-1.7B (text) and LFM3-VL-2B (vision), verified against the reference HF implementation llama/31252 LFM3-Audio-2B and LFM3-Omni-2B: ASR, TTS and voice chat from a single model, with streaming audio input and output llama/31257 API changes DRY sampler: new LLAMA_DRY_MAX_SEQ_BREAKERS (64) caps distinct sequence breakers, each costing O(n_vocab) at init llama/31035 mtmd : new experimental mtmd_audio_stream API turning PCM fed as it arrives into decoder-ready embedding rows llama/30629 mtmd : audio generation is now stateful - mtmd_gen_state replaces the raw state_data buffers of the audio gen API llama/30902 mtmd : mtmd_caps gained gen_audio ; new TTS types SOPRANO and LFM3A ; repetition penalty for sampled codes llama/28607 llama/31257 mtmd_helper_get_capabilities() to query the capabilities of an mmproj file from helper code llama/31183 Server: new /v1/realtime endpoint implementing the OpenAI realtime protocol for conversation and transcription llama/31269 llama/30636 Server: new POST /tts endpoint for text-to-speech models llama/26603 Server: reasoning effort levels of the chat template are exposed and selectable via the API llama/31271 Chat API: support for deferred tools and tool_reference content parts llama/31256 CLI: --model or -hf is now required llama/31242 New models LiquidAI LFM3-1.7B, LFM3-VL-2B, LFM3-Audio-2B, LFM3-Omni-2B llama/31252 llama/31257 LiquidAI d1-2B and d1-omni-2B decision models llama/31275 DeepSeek V4.1 Flash llama/31086 SenseNova U1 llama/28919 Beam (Reflection) llama/30670 Kolibri-1 (Aleph-Alpha) llama/30673 Flint llama/30928 Muse Spark Open (text, vision and audio) llama/30616 Granite Switch Decision, including the 256-way decision head llama/30676 llama/30693 Nemotron-3(.5)-Embed, with non-standard GQA and BPE tokenizer support llama/30877 llama/23343 H2O-Lightning-4B decision model llama/30361 MiniCPM-OCR 1.0 and MiniCPM-OCR-Jev llama/30979 llama/30980 Soprano TTS llama/28607 LFM2 short-conv and FFN blocks moved into a shared LFM base reused by newer LFM models llama/30874 Core changes MoE experts kept in host memory now use a 50/50 SLRU cache instead of a plain LRU cache llama/30637 Sparse attention: fused QSA mask op, QSA/DSA selection built without kq_mask , k-pool views shared between layers llama/30640 llama/31009 llama/30965 llama/31243 llama/30613 MoE: amax rescaling enabled for laguna , and -sm tensor denied on arches that use it llama/31147 llama/31081 Memory: no_alloc respected in all memory caches, moved out of llama_hparams , obsolete n_pad dropped llama/31087 llama/31141 llama/31200 Vocabulary loading optimized; d2t placed next to its set_rows use so it can stay on the GPU llama/30679 llama/30912 Tokenizer: new clean_spaces and metaspace prepend-scheme GGUF keys, hybrid DNA tokenizer fixes llama/30940 llama/30825 Tokenizer: Tekken pre-tokenizer for Pixtral, \p{M} in Tekken/GPT-4o lookaheads, Nemotron-3.5-Embed tokenization fix llama/30960 llama/30845 llama/30974 Grammar: recursion depth limited (and enforced) to prevent stack overflow; deep JSON rejected before walking it llama/29755 llama/31153 llama/30242 Qwen: merge tensors on convert, 2D output reshape, Qwen3 bidirectional attention and dense_2 output projection llama/31028 llama/30823 llama/30607 Speculative decoding: persist the dynamic ngram cache, probabilistic DFlash2 drafts, optional DFlash FC input scale llama/22055 llama/30663 llama/30945 llama/30927 LoRA: support for prism.hadamard folded weights llama/30910 Tensor parallel: stepfun and laguna now support 4-10 GPUs llama/24554 GGUF tools reject truncated tensor data in split , export-lora and merge llama/30497 llama/31044 llama-quant : fix 4D tensor quantization with ggml_nrows() and name-based expert detection llama/30820 convert-hf : faster endian conversion with more datatypes, text-only checkpoints in pplx-decider llama/30647 llama/30575 convert-hf : fixes for Granite speech tensors, Granite Switch MultiSwitch block count, Mistral-format DeepseekV2 llama/30628 llama/30621 llama/30669 Common: honor HTTP_PROXY / HTTPS_PROXY , allow concurrent downloads, pin model resolution on real HF repo layouts llama/21752 llama/29312 llama/30548 Multi-modality changes Streaming audio input via mtmd_audio_stream , used to support voxtral-realtime llama/30629 Soprano TTS support and MiniCPM-OCR 1.0 support llama/28607 llama/30979 Image preprocessing aligned with transformers/torchvision: LFM2 resize, tiles and layout, Qwen-VL resize llama/30943 llama/30261 llama/30736 LFM2 tiling parameters are read from the GGUF metadata llama/30840 lightonocr defaults to native resolution instead of forcing a 1540 longest edge llama/30600 build_inp_temporal_merge moved to the mtmd base class; fix Gemma-4 FFN activation llama/31065 llama/30882 Server changes Realtime conversation and transcription on /v1/realtime , with response.done sent after the committed audio drains llama/31269 llama/30636 llama/30994 POST /tts endpoint for TTS models llama/26603 Expose the reasoning effort levels of the chat template llama/31271 Router: configurable device memory margin for dynamic unloading of models llama/21231 Router: propagate client disconnects to the child task, stop re-adding the mmproj margin on sleep/resume llama/29707 llama/28233 Rerank endpoint accepts typed content input and substitutes the placeholder from the original template llama/29625 llama/30864 Anthropic /v1/messages : forward llama.cpp sampling params and pass id_slot through the conversion llama/30856 llama/28554 Support logprobs together with speculative decoding llama/27196 Fix usage.completion_tokens undercounting with n > 1 and missing output_index in Responses API SSE events llama/29486 llama/30863 Fix SWA checkpoint invalidation logic llama/30666 New --connect flag to allow p2p access to the server outside the LAN llama/28277 UI changes Discover and download models directly from HF Hub, with org-less models listed first llama/29584 llama/31215 New search dialog for conversations and messages llama/31173 Conversation compaction to keep long chats within the context llama/27401 Models manager moved to its own route, model details open in a drawer without leaving the page llama/30988 llama/31176 Reasoning menu built from the chat template's effort levels, with a clearer highlighted toggle llama/31273 llama/31212 Support OGG audio attachments by converting them to WAV llama/31237 New "Show tool call in progress" setting llama/30681 Save and reset settings buttons shown only when there are unsaved changes llama/31248 Sidebar resizing and general layout/UX improvements llama/31119 llama/31030 Fixes: draft lost after "Add System Message", system row stretching in WebKit llama/31214 llama/31246 Fixes: clipped attachment text preview, markdown tables and lists cut off on phones llama/30806 llama/30687 ggml changes Bumped from v0.27.0 to ggml v0.28.0 New GGML_OP_TOP_K_MASK fused sparse-attention mask, plus accessors for the precision configured on a compute node -1 is now a valid expert index in MUL_MAT_ID / ADD_ID : the slot is skipped and the output row zeroed SCALE accepts non-contiguous row views; SUM accepts non-contiguous inputs on CPU, CUDA, Vulkan and WebGPU Backends: fused MoE top-k and gate/up+GLU with chunked graph launches on CUDA, graph record/replay on SYCL Backends: Q2_K/Q3_K weights and a lightning indexer on OpenCL, subgroup reductions and src1 precision on Vulkan More: restructured Hexagon HTP backend, flash attention on ZDNN, Q2_0 on WebGPU, KleidiAI SVE GEMV/GEMM kernels Assets Nightly build: b11960 More info Releases and versioning of ggml-org projects Changelog since v0.7.0 8642541 llama.cpp : bump version to 0.8.0 ( #31309 ) d4f1b18 mtmd: enable video input support for LFM3 model family ( #31283 ) d1eb0de server : support tool calls in /v1/realtime ( #31287 ) 5d7793d sync : ggml ec941ee ggml : bump version to v.28.0 (ggml/1676) e486a4b ui: build the reasoning menu from the template effort levels ( #31273 ) f1a7dea tests : adjust constants to reduce irrelevant warnings ( #31254 ) a7af149 cuda : add top-k MoE fusion for 384 experts ( #31288 ) 2864937 vulkan: clamp A prefetch to end_k in coopmat1 int8 matmul ( #30283 ) a71c00f chat : stop qwen3-coder reasoning and content before template separators ( #30557 ) f4d8af6 ui : show save and reset settings buttons only when relevant ( #31248 ) 02d502f ui: Support OGG audio attachments by converting them to WAV ( #31237 ) b1756b2 ui: Fix draft for new message disappearing after using "Add System Message" action ( #31214 ) 6886628 ui : Search dialog ( #31173 ) 8ca4060 server : add realtime conversation and transcription on /v1/realtime ( #31269 ) d05706b model : add LiquidAI/d1-2B and LiquidAI/d1-omni-2B ( #31275 ) 1b4554e server: expose the reasoning effort levels of the chat template ( #31271 ) a919179 tests: fix CI riscv timeout in test-llama-context ( #31265 ) 338fce6 HIP/CUDA: remove pragma unroll from loops in conv2d where itteration count cant be infered at compile time ( #31255 ) 19ff817 model : add LiquidAI/LFM3-Audio-2B and LiquidAI/LFM3-Omni-2B ( #31257 ) eb7818c common : support deferred tools and tool_reference content parts ( #31256 ) 6c44591 snapdragon: switch QDC artifact upload and log download to v2 API ( #31240 ) 19cce69 model : add LiquidAI/LFM3-1.7B and LiquidAI/LFM3-VL-2B ( #31252 ) e86f5fd cmake: WASI doesn't support spawning ( #30751 ) 27b7a8a llama : build the k-pool sparse selection independently of the kq_mask shape ( #31243 ) 7ecb57f rpc : catch std::length_error in recv_msg ( #31204 ) 8542e94 tests : speed up tensor data generation and model saving ( #31145 ) 922f53e vulkan: fix CI llvmpipe by allowing dim 3 broadcast in MUL_MAT ( #31239 ) 0c8c59e mtmd-cli: Reduced scope of batch pointer ( #31155 ) ( #31165 ) 3ab37ae ui: fix system message row stretching to full prompt height in WebKit ( #31246 ) 85cc432 server: add router device memory margin parameter for dynamic unloading ( #21231 ) 74a1fd3 common : --model or -hf is required ( #31242 ) 7eed6b7 model: Add MiniCPM-OCR-Jev ( #30980 ) 2763785 metal : add GGML_OP_TOP_K_MASK ( #31230 ) d78f40d glm5-next : QSA without kq_mask (+ DSA) ( #31009 ) fae9ac5 ci : use ccache depend mode for ROCm release builds ( #31231 ) a8276b7 ci : force python 3.12 on ubuntu 26.04 ( #31222 ) de5122d ggml : relax scale to non-contiguous views ( #31146 ) 6666a73 tests : fix multi-seq split replay and partial-state cases for trained models ( #31216 ) 7a2e5ab llama : remove obsolete n_pad from memory instances ( #31200 ) 0d5ca60 ui: list org-less models first in the model selector ( #31215 ) d930fe3 opencl: refine mul mat id -1 index ( #31170 ) a2b3e12 opencl: initial support for q3_k ( #31172 ) 823df7d ui: Highlight reasoning toggle on hover and align it with model selector ( #31212 ) 1a97e38 ui: add conversation compaction ( #27401 ) bc262f3 ui: Open model details in a drawer without leaving the page ( #31176 ) f5892ca ui: use shared confirmation dialog for conversation deletion ( #31187 ) 7aca0d2 hexagon: add GGML_HEXAGON_VTCM_SIZE ( #31221 ) 961c376 llama : enable moe amax rescaling for laguna ( #31147 ) 4244ad7 ci : add windows behavior check ( #31191 ) 63b4b30 opencl: write KV-cache views in set_tensor so a state restore is not dropped ( #30471 ) caa8191 hexagon: MUL_MAT_ID row skipping optimizations and improvements ( #31169 ) a469940 llama : move no_alloc out of llama_hparams ( #31141 ) 4b851fb models : replace ggml_tensor** out-params with output structs ( #31142 ) 4d71b42 ggml-cpu : rewrite concat as one row kernel for all types ( #31179 ) 70c5f26 vulkan: rms norm optimization using subgroup reductions ( #29882 ) 5cd62ff sycl: template the plain MMVQ launch triples ( #31013 ) 38645c2 sycl: template the per-quant concat impls ( #31008 ) 02269b4 sycl: add set_tensor_2d for faster tensor-split loading ( #30358 ) 5320c87 sycl : bound reorder temp memory to 32 MiB ( #31062 ) 74b104c common: pin model resolution on real HF repo layouts ( #30548 ) c6fb3b5 mtmd: add mtmd_helper_get_capabilities ( #31183 ) 8b28c23 ggml-cpu : fix unused variables in arm arch ( #31180 ) fd8f845 tests : refactor test-llama-archs to not link internal libllama symbols ( #30880 ) 9125a2e ci : fix race in webgpu memset ( #31162 ) 9b8446b metal : stop overflow from happening in large matrix output offsets ( #30072 ) dc9e3be ui: UX improvements ( #31030 ) 69b3cc4 ui: Sidebar resizing improvements ( #31119 ) 224d94c ci : bump server timeout during startup ( #31174 ) 48c3611 ci : drop the macos-latest-x64 job ( #31175 ) a074215 deepseekv4.1: follow-up review fixes ( #31137 ) d854d98 cuda : use std::string instead of VLA for archName ( #30463 ) 48c9f08 common, grammar: add recursive depth limit, make it a requirement ( #31153 ) 6050b46 tests : adjust default threads for test-llama-context ( #31157 ) 2280f0f qwen: merge tensors on convert ( #31028 ) 1a0b56c ci : disable test-llama-context with fa off in the webgpu ( #30977 ) 63412d8 llama: fix exhausting CPU and MEM caused by dry sequence breaker ( #31035 ) 5c965fd llama-quant : fix 4D tensor quantization using ggml_nrows() and name-based expert detection ( #30820 ) f1168ac grammar: limit recursion depth to prevent stack overflow ( #29495 ) ( #29755 ) fa3645f llama : respect no_alloc in all memory caches ( #31087 ) 7790a92 tools : reject truncated GGUF tensor data in merge ( #31044 ) c49edf0 CUDA: fuse FFN gate/up matmuls and GLU in MMQ with interleaved gate/up rows ( #29948 ) a55c16e ggml-cuda: fuse qwen MRoPE + set-rows ( #31025 ) e321bda vulkan: Add a larger tile size for conv3d (coopmat2 only) ( #29920 ) 459a1ba vulkan : one warp tile per subgroup in the small matmul tiles ( #30106 ) f0fb598 hexagon: generic dims collapse/reshape for unary, binary and matmul ops ( #31071 ) 9a4580b opencl: add topk and lightning indexer ( #31026 ) b083c38 opencl: add initial q2_k support ( #30999 ) 344be0a ci : update CPU job assignments ( #31136 ) b3fa699 chat : reject JSON nested more than 128 levels before walking it ( #30242 ) 74bca39 model: DSV4.1 flash ( #31086 ) d327bf1 jinja : fix select and selectattr argument handling ( #31059 ) 78a8ae1 hexagon: KV-head team split for multicore HMX flash attention ( #31055 ) f3269ef server: refactor server entrypoint ( #31113 ) 3f03b17 metal : remove mul_mm_id amax rescaling ( #30924 ) 9a0fde9 rpc : add bounds check in rdma_recv ( #30399 ) e168e04 ui: Models Manager as Route + UI improvements ( #30988 ) ea1d7d6 fix(ui): align hover card and context popup styling with dropdown menu ( #30978 ) 71255fe ci : pass per-runner results dir to self-hosted jobs on T4 runners ( #31100 ) 73adf89 minimax-m3 : forward quant scales to the graph (fixes #31063 ) ( #31097 ) df9beac tests : fix test-llama-context for large n_batch ( #31083 ) 4d32b29 ci : exclude test-speculative-rejection-sampling from macos-latest-arm64 ( #31088 ) 3032209 llama : deny -sm tensor for arches with moe amax rescaling ( #31081 ) 701fd25 ggml : allow MUL_MAT_ID -1 index to skip the computation ( #26631 ) 3642238 tests : add speculative rejection draft sampling test ( #30213 ) 6b9ba4f ci : fix data race between runners sharing the model cache ( #31046 ) 8e5a58d vulkan: ggml src1 precision support ( #30656 ) 1ddffe9 HIP: add byte permute fallback when __builtin_amdgcn_perm is unavailable ( #30915 ) 7894e8b mtmd: move build_inp_temporal_merge to base class ( #31065 ) edc3538 mtmd : lfm2 resize matches torchvision ( #30943 ) 9ae73e6 mtmd : add Soprano TTS support ( #28607 ) 0ae0e19 hexagon: add SGN op ( #30346 ) 21ec307 common : allow concurrent downloads across processes ( #29312 ) 9145ddb hip: fix bf16 WMMA operand vector type for gfx11/gfx12 ( #30885 ) 1a24df1 ggm-cuda: Enforce DP4A MMQ tile height multiple of warp size ( #30837 ) 9ff0d7e CUDA: fix build after chunked CUDA graphs ( #30804 ) ( #31053 ) 06230cb allows the usage of 4-10 gpus for stepfun and laguna in tensor parallel ( #24554 ) 5c31142 qwen4exp : build the QSA selection without the kq_mask ( #30965 ) da2ee1e vendor : update LibreSSL to 4.4.0 [no ci] ( #31049 ) 280141e CUDA: chunk graphs to amortize graph launch ( #30804 ) 36e36e6 hexagon: add CEIL op ( #31006 ) e1e3b2c ui : bump packages to clear npm audit ( #31038 ) 4231b23 ggml : fix time overflow in ggml_time_us ( #30969 ) f00c908 ci : add behavior check workflow ( #31036 ) f5027fb CANN: missing const qualifiers added for consistency ( #30933 ) f64a498 sycl : pass device into mul_mat_uses_onednn ( #31014 ) 1ab09d6 Extend probabilistic sampling for DFlash2 drafts ( #30663 ) f9599d0 vocab : fix Nemotron-3.5-Embed tokenization ( #30974 ) 643b0cd hexagon: Op Fusion refactoring, optimizations and new fusions like BINARY_NX (back-to-back ADDs, etc) ( #30843 ) 0a9ef00 sycl: Replace host waits in fattn-mkl with explicit dependencies ( #30684 ) 7377bad sycl: Add graph record and replay ( #28725 ) 184f653 server: Substitute rerank placeholder from the original template only. ( #30864 ) d814cbb server: realtime API: send complete after committed audio drains ( #30994 ) 970b51c opencl: add depthwise conv2d ( #30900 ) a08ab75 mtmd : add MiniCPM-OCR 1.0 support ( #30979 ) 19ab5a5 clef : include for std::find and std::copy ( #30981 ) 36cbf41 Fix !30793 5c19a5a glm5 : optimize inputs ( #30932 ) d9ee007 model : fix qwen4exp layer inputs for DFlash drafters ( #30927 ) d81d0d8 Multi-column on Intel XMX matrix engines refactored ( #29864 ) d772569 vulkan: replace std::aligned_alloc with posix_memalign for termux compatibility ( #30828 ) 0693dbf nemotron : support non-standard GQA, BPE tokenizer and domyn-small pre-type ( #23343 ) a5d2227 server : support typed content input for RERANK endpoint ( #29625 ) 5f5acfe ci : disable slow WebGPU tests ( #30963 ) 1f4c2ee ci : be able to reconfigure HTTP port for server pytest workers ( #30972 ) 7170cad sycl: fix CONV_2D wrong results for non-contiguous input ( #30363 ) d88040c vocab : add clean_spaces GGUF key ( #30940 ) e197cef vocab : use Tekken pre-tokenizer for pixtral rather than the Llama 3 one ( #30960 ) bf039c8 models : Record layer inputs for all granite models ( #30957 ) dfeea52 kleidiai : add Q8_0 SVE dotprod GEMV and SVE i8mm GEMM kernels ( #30808 ) e3797b1 sycl: merge the fp16 and fp32 dequant switches ( #30740 ) 0b1281a webgpu : add Q2_0 support ( #30914 ) 4912ac2 dflash : load optional FC input scale ( #30945 ) 84746c5 ui: Add "Show tool call in progress" setting ( #30681 ) 0682a57 lora : support prism.hadamard folded weights ( #30910 ) a6b83d4 ui : key draft sidecar badges by model instead of repo ( #30919 ) c7fc509 opencl: add F32-to-I32 ARGMAX ( #30897 ) a37cc46 models : add Flint model (FlintForCausalLM) ( #30928 ) 99fb997 jinja : fix namespace attributes shadowed by dict methods ( #30941 ) 7775ffb model: Add support for SenseNova U1 model ( #28919 ) d454a20 llama: create new fused op for QSA mask ( #30640 ) 0756e83 sycl: q8 fast dequant ( #30775 ) 9febe63 jinja: support hexadecimal string escapes ( #30929 ) 9b56ccf ggml-opencl : add IM2COL_3D support ( #30895 ) 0a1ef30 mtmd: add state object for mtmd_gen ( #30902 ) 261700b server : forward llama.cpp sampling params on /v1/messages ( #30856 ) f849095 vendor: update BoringSSL to 0.20261020.0 ( #30889 ) 824eaec llama : optimize vocabulary loading ( #30679 ) eb182d8 llama : place d2t by its set_rows use so it can stay on the GPU ( #30912 ) ea9e344 metal : fix memory leaks and cleanup logic in GPU capture path ( #30890 ) 0efe8e4 hexagon: neon-vectorized and threaded repack (tiling) ( #30901 ) b531e4c opencl: add dp4a GEMM variants to vector load activation ( #30753 ) 74b115c sycl : fix fa crash for Query head dimension mismatch (neq0 != HSK / D=2048/4096) ( #30286 ) 96caa80 sycl: collapse duplicate need_check launch bodies in mmq ( #30739 ) 479a527 ggml-cpu : compute f32 gelu_quick and geglu_quick without the fp16 table ( #30737 ) 8baabd5 llama : scale moe down projection per expert token ( #30861 ) 493253f Sycl iq3 crash fix ( #30604 ) 339f324 opencl: fix rope program build error with newer Clang ( #30893 ) 9a3b91c server : fix usage.completion_tokens undercount with n > 1 ( #29486 ) 5c0b49a server : add POST /tts endpoint for TTS models ( #26603 ) 1242be6 server: add realtime transcription API ( #30636 ) 84e66d0 refactor : move LFM2 shortconv and FFN blocks into a shared LFM base ( #30874 ) 52ffa02 model : support Nemotron-3(.5)-Embed ( #30877 ) 839a572 qwen: reshape output to 2d instead of 3d ( #30823 ) ead9f32 server: Support logprobs with speculative decoding ( #27196 ) b684b49 hexagon: fix VTCM size query on images that need layout out-params ( #30655 ) 4a45de4 mtmd : lfm2 tiles and layout match transformers ( #30261 ) 7e3eeee model : add H2O-Lightning-4B decision model ( #30361 ) 5ba3b9f mtmd: fix gemma 4 ffn act ( #30882 ) 5a9a34d server : avoid repeated mmproj memory margin addition on sleep/resume ( #28233 ) 39da130 ggml-cuda : support ssm_conv kernel size 7 ( #30873 ) 4e20138 server: Router wasn't propagating the client disconnects fully to the child, the response wait could cause a delayed cancellation ( #29707 ) 1ba568c server: fix missing output_index in Responses API SSE events for compatibility ( #30863 ) 36140db mtmd : read LFM2 tiling params from GGUF metadata ( #30840 ) df11702 metal : optimize argmax and pool_1d ( #30862 ) 9df0b73 model : drop the redundant precision overrides in the Kolibri-1 router ( #30865 ) b38960f ci : remove superfluous webgpu jobs ( #30868 ) a01ce9f opencl: add several gemm variants for small batches and some fixes ( #30850 ) 8115b4c sycl : replace memset due to not always ordered ( #30812 ) 119f68d ggml-cpu : select the NEON fp32->fp16 conversion ( #30505 ) b684498 HIP/CUDA: Fix reduction in mmf getting tile widths not devisiable by 64 ( #30836 ) 522f2b6 ggml-zdnn: introduce flash attention op ( #30512 ) 83c2d01 spec : save the dynamic ngram cache file ( #22055 ) 13786fb CUDA: Clear CUDA graphs after legacy memory pool flush ( #26771 ) d806193 server : pass id_slot through the Anthropic /v1/messages conversion ( #28554 ) 704366d metal : fix missing MoE kernel variant for 9 experts per token ( #30610 ) ( #30699 ) 707616f ci: Fix --strict mode for API check ( #30623 ) d8d9297 vocab : add \p{M} to lookaheads in Tekken and GPT-4o pre-tokenizer regexes ( #30845 ) 7879491 tests : make MoE router selection independent of the backend noise ( #30818 ) 8466395 hexagon: update to snapdragon-toolchain v0.8 and enable hexagon v85 ( #30854 ) dd002b9 sycl: fix compiler warnings - missing prototypes, dead code, extra semicolons ( #30271 ) 1d88cb0 ui: hide the native clear button in SearchInput ( #30719 ) 3bb63cb sycl : fix get_rows on reordered quantized weights ( #30430 ) f711c8f mtmd : match the transformers Qwen-VL resize ( #30736 ) 921257f ci, docs: add WASI CI and docs ( #30754 ) 3ffb629 ci : re-enable type/lint-check for skills ( #30713 ) 7adf160 server: add --connect, allow p2p access to server outside LAN ( #28277 ) ab7ed0d ui : fix attachment text preview clipped when a line is longer than the container ( #30806 ) 4c3c581 hybrid dna tokenizer fixes ( #30825 ) 1b29621 opencl: add cooperative-k dp4a gemm for q4_0, q4_k and q6_k ( #30741 ) 6fa4f6c opencl: add get_rows for i32, cpy for i32 and f32 ( #30756 ) 0ce8cd1 jinja : implement unique filter ( #30819 ) f174553 server : fix swa checkpoint invalidation logic ( #30666 ) 7951f60 vendor : update cpp-httplib to 0.62.0 ( #30785 ) 33d6135 moe-cache : replace MoE LRU cache with a 50/50 SLRU cache ( #30637 ) 098ce52 metal : fix moe_reduce fusion race when dst aliases its inputs ( #30795 ) f3fb2fc cann : refactor #ifdef blocks to avoid unreachable code after return ( #25273 ) fda00f1 tests: add big-endian conversion tests ( #30705 ) 4866db3 CUDA: fix warning for nonexistent extra semicolon ( #30774 ) 42b7003 ggml-cpu: vectorize ggml_v_silu and ggml_v_expf ( #30791 ) 4c1004c cuda: cap MMQ Stream-K blocks at available work ( #30553 ) 412a363 qwen3 : bidirectional attention and dense_2 output projection ( #30607 ) 2b57148 ui: Fix markdown tables and lists being cut off on phones ( #30687 ) 8f97d82 tools : reject truncated GGUF tensor data in split and export tools ( #30497 ) 27af581 tests : update Metal fusion baseline for beam ( #30764 ) 7db0d3d pi : turn .pi/gg into a system prompt addendum ( #30762 ) 99db719 CUDA: fix shared-memory WAR hazard in flash_attn_ext_vec ( #30573 ) 31288c9 hexagon: FLASH_ATTN_EXT improvements for longer context and SWA models ( #30731 ) fe8841a hexagon: allow multistream FA ( #30218 ) ff5a233 cuda : fuse qwen4exp's SCALE -> SIGMOID -> SCALE -> hc_post chain ( #30602 ) 0878f7c ggml: support non-contiguous SUM (CPU, CUDA, Vulkan, WebGPU) ( #28851 ) 5aeac37 ggml-cuda: fattn do not check oob if k_VKQ_max = (k_VKQ_max - nbatch_fa) ( #30572 ) 547208d Restore ESIMD kernels on FFN path ( #30239 ) 848bbda hexagon: add support for hadamard MUL_MAT and GET_ROW for flat and tiled Q1_0 and Q2_0 ( #30627 ) 797de63 hexagon: add support for Q1_0 and Q2_0 ( #30122 ) 9d1878a ggml-cuda: HIP: use __builtin_amdgcn_perm for q1_0 unpacking ( #29927 ) c0fd786 ui : Discover & Download Models from HF Hub ( #29584 ) 2744e48 CUDA: faster MMVQ for low-bit types ( #30517 ) 10b8b75 tests: give the random model generator a per-tensor filler table ( #30674 ) 9d1e036 cuda : fix -Wtautological-compare in fattn vec dispatch ( #30519 ) f2f667b cuda : add grouped experts top-k fusion ( #29181 ) 62318cd model : add Kolibri-1 (Aleph-Alpha) support ( #30673 ) 83f9389 ci : added ABI reports as github artifact ( #30619 ) 1268eda model : Granite switch decision 256 options ( #30693 ) f74e2fa sycl: fix prompt-processing regression after Q4_0/Q8_0 weight reorder ( #30374 ) ea0c4c2 skills: add slice-model ( #30677 ) 6420cf5 ci: update device matrix for Snapdragon jobs by removing SM8750 ( #30620 ) 27c7a76 hexagon: vectorize softplus with HVX ( #30435 ) 2f2763d opencl: Add MxFP4 MoE bin kernel for Adreno X1 devices ( #30691 ) 01fc3aa model: add Beam (Reflection) ( #30670 ) 23f7aab model : Granite Switch Decision ( #30676 ) 7182ef7 common: honor HTTP_PROXY/HTTPS_PROXY env vars in http client ( #21752 ) 2a66703 convert : respect Mistral format for DeepseekV2Model ( #30669 ) f336359 Add more benchmarks to llama-eval ( #26174 ) ceefd16 hexagon: correct HMX FA sinks ( #30581 ) 9a16f1d model : MTP support for Mellum2.1 ( #30612 ) b84ea5c convert : speed up model endian conversion and add more datatype support ( #30647 ) a30fb49 [SYCL]: fix memory errors in mul_mat, split buffer, host pool ( #29889 ) 495c580 gguf-py : add numpy Q1_0 and Q2_0 de/quantization support ( #30630 ) 623c163 CUDA: HIP: rms_norm: add variants that load float4 at a time and store x in registers ( #29720 ) 13b8048 common : read ngram cache parts by reference instead of copying ( #30061 ) 0f43762 convert : support text-only checkpoints in pplx-decider ( #30575 ) 3dbcb7f cpu : reduce AVX2 tiled accumulators together ( #30296 ) c804754 ggml-cpu: refactor s309x repack helper functions ( #30588 ) c0083e3 sycl : reduce the build threads to half ( #30236 ) 13de11e sycl: wide stores for the q4_K/q5_K weight dequant ( #29696 ) 88aaf32 tests : catch vanished rows in the fusion baseline ( #30618 ) a8d9a7e vulkan: fix gpu-visible host memory issues ( #30468 ) f12aaa3 Fix failing RocM tests ( #30611 ) 5e03a1f graph : add precision handling for MELLUM architecture ( #30584 ) b797b9c hexagon: tensor repacking rework and support for tiled and flat quantized and fp weights ( #30635 ) 6afa9a3 llama : share the k-pool input views between layers ( #30613 ) b6334e3 Limit max CUDA pinned host buffer size to 4 GB ( #30449 ) e707790 sycl: support reordered Q8_0 MoE weights ( #29337 ) 43d57fb [SYCL] Enable ssl in build script and CI ( #30456 ) 2851b3b mtmd: add mtmd_audio_stream + support voxtral-realtime ( #30629 ) 59d5fad convert : fix Granite Switch block_count for MultiSwitch checkpoints ( #30621 ) e287bd8 convert : fix regression in mapping of Granite speech tensors ( #30628 ) 2f729cf mtmd: lightonocr does not require longest edge to always be 1540, native resolution is the default ( #30600 ) ba3c05f model: add Muse Spark Open (text, vision and audio) ( #30616 ) b76b133 pi : expand AI disclosure with hardware and stats ( #30615 )

AI models and agent tools DeepInfer — An inference framework for running DeepSeek models on large GPU systems. https://github.com/deepseek-ai/DeepInfer Recurrent Looped Transformer — A language-model architecture that carries internal state from one token to the next. https://github.com/yifanzhang-pro/recurrent-looped-tranformer Anatomy — An agent skill that creates interactive illustrations of machines and complex systems. https://github.com/wheresryan22/anatomy RSI-Anything — A research framework that uses predicted outcomes and external feedback to improve agent workflows. https://github.com/Gen-Verse/RSI-Anything solidcv — A Rust library for computer vision, 3D reconstruction, and AI model analysis. https://github.com/solidsf-inc/solidcv Harness² — A framework that improves an agent’s prompts, tools, and workflow while keeping model weights fixed. https://github.com/google-research/harness2 GroundAnything-VLM — A vision-language model that locates objects and image regions from text instructions. https://huggingface.co/GroundingPI/GroundAnything-VLM GLM-5.3 Cybersecurity FP8 — A third-party GLM-5.3 release adapted for cybersecurity tasks. https://huggingface.co/dealignai/GLM-5.3-CYBERSECURITY-FP8 DeepSeek-V4.1-Flash Uncensored FP8 — A third-party DeepSeek release modified to reduce refusal behavior. https://huggingface.co/dealignai/DeepSeek-V4.1-Flash-1017-UNCENSORED-FP8 Qwen3.8-27B Uncensored GGUF — A GGUF release for local model runtimes. The uploader labels it “uncensored.” https://huggingface.co/orcarouter/Qwen3.8-27B-Uncensored-GGUF Genome models Evo 2 — DNA language models for analyzing and generating genome sequences. These links provide the 40B and 7B versions. 40B: https://huggingface.co/arcinstitute/evo2_40b 7B: https://huggingface.co/arcinstitute/evo2_7b Genos — Models trained on human genomes to study patterns in DNA sequences. Available in 1.2B and 10B versions. 1.2B: https://huggingface.co/BGI-HangzhouAI/Genos-1.2B 10B: https://huggingface.co/BGI-HangzhouAI/Genos-10B Carbon — Hugging Face’s genomic models, with code for evaluation and further training. https://github.com/huggingface/carbon Tissue-image models OpenMidnight — A model that extracts features from tissue images for pathology research. https://huggingface.co/SophontAI/OpenMidnight GenBio-PathFM — A model for analyzing tissue images, trained on publicly available pathology data. https://huggingface.co/genbio-ai/genbio-pathfm Protein models BoltzGen — A model for designing proteins and peptides that bind to selected molecules. https://huggingface.co/boltzgen/boltzgen-1 Pinal — A framework that generates candidate protein structures and sequences from written instructions. https://huggingface.co/westlake-repl/Pinal ESM-2 and ESMFold — ESM-2 models protein sequences. ESMFold predicts a protein’s 3D structure from its sequence. https://github.com/facebookresearch/esm OpenFold — A trainable implementation of AlphaFold 2 for protein-structure prediction. https://github.com/aqlaboratory/openfold Research archives arXiv Complete Corpus — A community archive of arXiv papers, including metadata, extracted text, source files, and PDFs. Select the files that fit your storage. https://huggingface.co/datasets/secemp9/arxiv-complete PubMed Central Open Access Subset — A collection of biomedical research articles available for reuse under their individual licenses. https://pmc.ncbi.nlm.nih.gov/tools/openftlist/ Security and public information tools ARTEX — An AI agent system that automates penetration testing and records security findings. https://github.com/BaaRai/ARTEX Ghidra — A software-analysis framework that helps researchers inspect compiled programs and understand how they work. https://github.com/NationalSecurityAgency/ghidra Cloudflare Security Audit Skill — A coding-agent skill that checks repositories for security flaws and verifies reported findings. https://github.com/cloudflare/security-audit-skill Blackbird — A tool that searches public platforms for accounts associated with a username or email address. https://github.com/antoniaci/blackbird Maigret — A tool that checks websites for a username and collects public account information. https://github.com/soxoj/maigret SpiderFoot — A tool that combines public data sources to map internet assets and exposed information. https://github.com/smicallef/spiderfoot theHarvester — A tool that collects public domain, hostname, email, and network information for security assessments. https://github.com/laramies/theHarvester Shodan Python — The official Python library and command-line tool for querying Shodan’s internet-device database. It requires Shodan access. https://github.com/achillean/shodan-python Radio hardware HackRF One — An open hardware radio device for receiving and transmitting signals from 1 MHz to 6 GHz. https://greatscottgadgets.com/hackrf/one/ submitted by /u/Lord_44th__Raikage to r/accelerate [link] [comments]

Article URL: https://formlabs.com/products/form-studio-1-basic-founders-edition/ Comments URL: https://news.ycombinator.com/item?id=50281044 Points: 169 # Comments: 108

Article URL: https://blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-4-carbon/ Comments URL: https://news.ycombinator.com/item?id=50276792 Points: 897 # Comments: 736