NVIDIA

A Reddit user ran DeepSeek-V4-Flash with vLLM on two ASUS GX10 DGX Spark nodes and reported 1,680 prefill tokens/s plus 39.8 decode tokens/s at a 256K context with MTP=2; the setup uses TP=2 over RoCE, fp8 KV cache, and fits about 1M tokens safely in KV cache.

Runway joined Cosmos Coalition as a founding member and will co-develop the first open world-model foundation model for physical AI with NVIDIA.

NVIDIA released the FOX factory operations blueprint at GTC Taipei, and Foxconn used it to build the MoMClaw multi-agent system with an expected 80% reduction in root-cause analysis time.

NVIDIA released Cosmos 3 as an open physical AI generalist model with native visual reasoning, world generation, and action generation, offering two variants: Super at 32B parameters and Nano at 8B parameters.

NVIDIA released RTX Spark, a Windows PC for local AI agents with 1 petaflops of AI compute and 128GB of unified memory. OpenShell uses new Windows security primitives with Microsoft, while llama.cpp optimizations raise Qwen 27B throughput by up to 2x.

Nvidia introduced one new PC-focused chip to enter the Windows laptop market and compete with Intel and AMD; the RSS snippet does not disclose specifications, pricing, launch timing, or AI compute metrics.

mudler_it ported NVIDIA Parakeet speech-to-text models to C++/ggml with no Python or PyTorch, reporting byte-for-byte NeMo parity on f32/f16, up to about 5x GPU speedups on larger TDT and hybrid models, and GGUF quantization across f16, q8_0, q6_k, q5_k, and q4_k.

Apple will present Siri and on-device AI upgrades at next month’s WWDC, with iPhones running a smaller Gemini-distilled model locally while complex queries route to Google Cloud using Nvidia confidential computing.

MouShen Intelligence released STI-WM, a spatiotemporally integrated world-action model for robotics, claiming support for RGB, point-cloud, and proprioceptive inputs, hundred-second task planning, and disclosing five funding rounds in six months plus a RMB 300 million Pre-A round.

NVIDIA, Microsoft, and Arm posted the same “new era of PC” teaser, and the article says the rumored N1X laptop may use a 20-core Arm CPU, a Blackwell GPU, 6,144 CUDA cores, and 128GB of LPDDR5X unified memory, while bandwidth and x86 translation remain the stated constraints.

Moushen Intelligence released STI-WM, a spatiotemporally integrated world action model for robotics, with RGB, depth point cloud, and proprioceptive inputs; the post says it supports hundred-second-scale long-horizon task rollout and closed-loop replanning, but does not disclose benchmark scores or deployment costs.

NVIDIA released DynoSim for optimizing its Dynamo inference serving stack; the Rust-based tool models thousands of deployment configurations on a single virtual timeline and reached 1,500x real-time speed in tests.

The author installed an RTX Pro 6000 Blackwell in a 2016 Dell PowerEdge R730 and claims a 650K-context local AI box; the post describes fan-shroud modification, dual-riser power, PCIe BAR allocation failures, ACPI/DSDT inspection, MMIO aperture work, and Linux PCIe boot-flag testing as required conditions.

SemiAnalysis says xAI dropped JAX GPU and moved to a C training framework written with Grok Build; the snippet claims xAI’s JAX stack had MFU below 10%, but the post does not disclose reproducible benchmark conditions.

NVIDIA, Tsinghua, University of Toronto, and Vector Institute released Gamma-World, a multi-agent world model using simplex-based positional encoding and hub tokens to cut interaction cost from quadratic to linear, with 8-player latency dropping from 17.6 ms to 4.5 ms.

Axios says Groq is seeking $650 million in internal funding while shifting from hardware toward AI inference, after Nvidia’s reported $20 billion not-acqui-hire; the RSS snippet does not disclose Groq’s valuation, investor names, deal structure, or fundraising timeline.

StepFun released Step 3.7 Flash with 196B total parameters, 11B active MoE, a built-in 1.8B ViT, and local execution on 128GB RAM.

Samsung Electronics has begun shipping samples of its most advanced memory to customers for AI accelerators from companies including Nvidia; the RSS snippet does not disclose the chip model, customer list, sample volume, pricing, or mass-production timeline.

NVIDIA Research presented 8 ICRA papers on sim-to-real robotics: ScheduleStream delivered a 3x speedup for multi-arm planning, COMPASS reached about 80% success across 20 real-world navigation trials, and Grasp-MPC achieved about 75% real-robot grasping success.

The title says Nvidia LocateAnything-3B performs vision-language grounding with parallel box decoding and runs 10x faster than Qwen3-VL; the post body only provides Hugging Face, GitHub, demo, and project links, and does not disclose benchmark setup or accuracy numbers.