Evidence brief
The repost shows NVIDIAAI introducing NVIDIA Nemotron 3.5 Lightning, an open 30B MoE model with 3B active parameters, designed for always-on agents scenarios.
The repost shows NVIDIAAI introducing NVIDIA Nemotron 3.5 Lightning, an open 30B MoE model with 3B active parameters, designed for always-on agents scenarios.
This brief preserves the original source so the summary and editorial context can be checked independently.
Source attributionX · @huggingface
Open the original sourceRelationships are derived from shared topics, entities, categories, tags, and community context; every result remains independently source-linked.
LTX launched the LTX-2.5 model with native ComfyUI integration; on a setup with 2 NVIDIA GB200s, generating a 10-second 720P video takes 6.8 seconds, and LTX-2.5 Fast is priced at $0.09 per second.
Original source@huggingface reposted ClementDelangue’s post saying “Local AI is exploding,” and mentioned that Hugging Face has been building Transformers.js for the past three years; the original post is truncated at “has now become…,” so the full conclusion is not shown.
Original sourceUnslothAI says 2-bit NVIDIA Nemotron 3.5 Lightning used only 22GB VRAM to run tool calling continuously for 10 minutes. During the process, the model cited more than 80 websites, executed code, and searched 10 real locations; it can be run and trained via Unsloth Desktop.
Original sourceThe post says NVIDIA researchers built SparDA, adding a Forecast projection beyond Q, K, and V to use the previous layer to predict the KV blocks needed by the next layer; this variant makes decoding 1.7x faster and improves long-reasoning accuracy by 6.5 points.
Original sourceSGLang and Miles supported Qwen3.8-2.4T-A95B on launch day; the model is Qwen’s largest open-source model, with 2.4T total parameters, 95B active per token, and a hybrid attention architecture.
Original source