🆕 [GitHub Repos] orgs/NVIDIA - dream-team


https://github.com/NVIDIA/dream-team

🔄 [GitHub Releases] turboderp-org/exllamav3 - 1.1.0


https://github.com/turboderp-org/exllamav3/releases/tag/v1.1.0

🆕 [HF Models] openbmb - MiniCPM-RobotTrack

https://huggingface.co/openbmb/MiniCPM-RobotTrack


🆕 [HF Models] openbmb - MiniCPM-RobotManip

https://huggingface.co/openbmb/MiniCPM-RobotManip

🔄 [GitHub Releases] PygmalionAI/aphrodite-engine - v0.22.0


https://github.com/dphnAI/sonar/releases/tag/v0.22.0

🗓️ Weekly GitHub Activity


🦙 llama.cpp
└ Release: b9966 → b10068
└ 102 commits

- Added support for Hunyuan 3 (hy_v3) with MTP speculative decoding #25395 #25641
- Added support for Minimax2 Eagle3 speculative decoding 259ae1d
- Added support for BitNetForCausalLM GGUF conversion #25769
- Implemented GGML_OP_LIGHTNING_INDEXER for DeepSeek V3.2/V4 on CPU and CUDA #24231 #25545
- Added fused hyper-connection ops for DeepSeek V4 to reduce graph splits #25585 #25702
- Added CUDA Virtual Devices support and enabled CUDA graphs on Volta and Turing architectures #25228 #25749
- Added Flash Attention via oneDNN graph API for SYCL on Intel Battlemage #25222
- Optimized CUDA MoE gate/up activation quantization, improving prefill times on RTX 5090 and Blackwell #25441
- Added auto-download of DeepSeek-Flash and Eagle3 speculative decoding sidecars from Hugging Face #25811
- Server now supports CORS configuration options and accepts null sampling parameters to request defaults #25655 #25538
- Added KleidiAI SME2 f32 kernel and improved hardware-specific kernel dispatch #24414 #25478
- Fixed CUDA crash when querying memory on devices with no available memory #25157
- Fixed Tensor Parallel execution for Phi3, Bert, Plamo2/3, and ChatGLM #25536
- Fixed quantization crash on DeepSeek-V4 i32 routing tables #25787

🔗 All changes | Latest release


🎨 stable-diffusion.cpp
└ Release: master-775-b5d8120 → master-782-b290693
└ 7 commits

- Support for AnimateDiff SD 1.5 motion modules v2 and v3 #1784 with img2video capabilities via the --init-img parameter #1789
- Support for ADetailer #1785
- Support for PiD 1.5 #1790
- Configurable reference image processing for edit models #1780
- Fixed cross attention and output projection token protection for Anima LoRAs #1786

🔗 All changes | Latest release


🤗 Fresh models trending on HuggingFace:

thinkingmachines/Inkling ♡1060
OpenMOSS-Team/MOSS-VL-Realtime ♡76
ai-sage/GigaAM-Multilingual ♡56
nineninesix/diamond-1.0 ♡43
ai-sage/GigaChat3.1-Audio-10B-A1.8B ♡38
rzgar/Bernini-R-S2V ♡37
acvlab/ABot-World-0-5B-LF ♡29
fal/ideogram-v4-instant ♡27
InternScience/Agents-A1-4B ♡26
sensenova/SenseNova-U1-8B-MoT-Infographic-V3 ♡26
OpenMOSS-Team/MOSS-VL-Instruct-0708 ♡23
fal/ideogram-v4-fast ♡23
t-tech/T-Search ♡23
GnLOLot/MiniCPM5-1B-Claude-Opus-Fable5-V2-Thinking ♡23
mente-ai/uyu-2-28B ♡20
OpenMOSS-Team/MOSS-VL-Base-0708 ♡17
yijunwang2/krea2-outpaint ♡17
yijunwang2/krea2-reid ♡15

📰 HuggingFace - Introducing Cosmos 3 Edge


https://huggingface.co/blog/nvidia/cosmos3edge

🔓 [HF Models] nvidia - Cosmos3-Edge

https://huggingface.co/nvidia/Cosmos3-Edge


🔓 [HF Models] nvidia - Cosmos3-Super-Text2Image-4Step

https://huggingface.co/nvidia/Cosmos3-Super-Text2Image-4Step


🔓 [HF Models] nvidia - Cosmos3-Super-Image2Video-4Step

https://huggingface.co/nvidia/Cosmos3-Super-Image2Video-4Step


🔓 [HF Models] nvidia - Cosmos3-Edge-Policy-DROID

https://huggingface.co/nvidia/Cosmos3-Edge-Policy-DROID

📰 Google AI Blog - Run Ray on TPU, Part 1: The foundations
Ray 2.55 introduces official, first-class support for Google Cloud TPUs, enabling developers to run distributed Python workloads on Google's accelerators using the familiar Ray task-and-actor APIs. To handle the strict networking requirement of keeping multi-host TPU "slices" together over their Inter-Chip Interconnect (ICI), the KubeRay Operator on GKE automatically provisions and labels the underlying hardware layout. Ray Core utilizes these labels via its slice_placement_group() primitive to atomically reserve complete slices, allowing developers to deploy jobs through KubeRay, Ray Train, or Ray Serve simply by declaring a hardware topology (like "4x4") without writing custom placement code.

https://developers.googleblog.com/en/run-ray-on-tpu-part-1-the-foundations/

📰 OpenAI - Safety and alignment in an era of long-horizon models


https://openai.com/index/safety-alignment-long-horizon-models

🆕 [HF Models] Motif-Technologies - Motif-3-Beta


https://huggingface.co/Motif-Technologies/Motif-3-Beta

📰 HuggingFace - Grabette: an open system to record robot-manipulation data


https://huggingface.co/blog/grabette

🆕 [HF Models] jdopensource - JoyAI-VL-Interaction


https://huggingface.co/jdopensource/JoyAI-VL-Interaction

📰 Google Model Cards - Gemini 3.6 Flash

https://deepmind.google/models/model-cards/gemini-3-6-flash/


📰 Google Model Cards - Gemini 3.5 Flash-Lite

https://deepmind.google/models/model-cards/gemini-3-5-flash-lite/

🆕 [HF Models] nvidia - NV-JEPA-DNA-HyenaDNA

https://huggingface.co/nvidia/NV-JEPA-DNA-HyenaDNA


🆕 [HF Models] nvidia - NV-JEPA-DNA-NTv3

https://huggingface.co/nvidia/NV-JEPA-DNA-NTv3


🆕 [HF Models] nvidia - NV-JEPA-DNA-DNABERT2

https://huggingface.co/nvidia/NV-JEPA-DNA-DNABERT2

📰 Google Gemma Blog - Scaling Agentic RL: High-Throughput Agentic Training with Tunix
Tunix is Google’s new JAX-native post-training library designed to eliminate TPU idling bottlenecks when training multi-turn, tool-using LLM reasoning agents. It maximizes hardware throughput by combining highly concurrent, asynchronous rollouts with a decoupled producer-consumer pipeline, ensuring the trainer is constantly fed even while agents wait on network I/O or environment steps. Additionally, Tunix provides plug-and-play abstractions and continuous macro-level profiling, allowing developers to easily integrate custom open-source environments and optimize complex distributed workflows without massive code rewrites.

https://developers.googleblog.com/en/scaling-agentic-rl-high-throughput-agentic-training-with-tunix/

🔓 xAI - Grok for Excel

https://x.ai//news/introducing-excel-addin


🔓 xAI - Grok for Outlook

https://x.ai//news/introducing-outlook-addin

📰 Claude Blog - How Anthropic secures its AI-native software development lifecycle

https://claude.com/blog/how-anthropic-secures-its-ai-native-software-development-lifecycle


📰 Claude Blog - How Datadog built a “universal machine tool” for Claude Code

https://claude.com/blog/how-datadog-built-a-universal-machine-tool-for-claude-code


📰 Claude Blog - Working at the frontier: How Rakuten builds agents overnight with Claude Fable 5

https://claude.com/blog/working-at-the-frontier-rakuten

📰 HuggingFace - The State of Simulation for Physical AI: An Overview


https://huggingface.co/blog/nvidia/state-of-simulation-for-physical-ai

📰 NVIDIA - Inside NVIDIA Rubin GPU Architecture: Powering the Era of Agentic AI
What began as discrete AI model training and human-facing chat interfaces has evolved into always-on AI factories dedicated to producing intelligence at scale.

https://developer.nvidia.com/blog/inside-nvidia-rubin-gpu-architecture-powering-the-era-of-agentic-ai/


📰 NVIDIA - NVIDIA Vera CPU: Olympus Cores Built for Maximum Single-Thread Performance in Agentic AI
Agentic AI shifts more of the critical execution path onto the CPU. Agents operate in sandboxes to execute code, invoke tools, retrieve context…

https://developer.nvidia.com/blog/inside-nvidia-vera-cpu-olympus-cores-built-for-maximum-single-threaded-performance-in-agentic-ai/


📰 NVIDIA - Setting a World Record for MoE Pre-Training on NVIDIA GB300 NVL72
Frontier model pre-training has converged on mixture of experts (MoE), which is fundamentally changing what limits large-scale AI training. As compute per token…

https://developer.nvidia.com/blog/setting-a-world-record-for-moe-pre-training-on-nvidia-gb300-nvl72/


📰 NVIDIA - NVIDIA NVLink: The Scale-Up Network for AI Factories
The demand for AI continues to accelerate. Workloads are getting larger, models are becoming more complex, and there is mounting pressure to deploy AI compute…

https://developer.nvidia.com/blog/nvidia-nvlink-the-scale-up-network-for-ai-factories/

📰 Qwen Research - Qwen-Image-3.0: Rich Content, Authentic Details, Deep Knowledge


https://qwen.ai/blog?id=qwen-image-3.0

🔄 [GitHub Releases] invoke-ai/InvokeAI - v6.13.7


https://github.com/invoke-ai/InvokeAI/releases/tag/v6.13.7