AI Dataset2026
Provides curated short video clips (49- and 81-frame) with layered ground truth—edit layers, alpha mattes, and composite targets—for training and evaluating content-preserving layered diffusion video editing. Contains background-replace and object-add edits; Apache-2.0 licensed.
AI Model2026
Multimodal image-text-to-text fork of Gemma 4 (31B) using a 'CRACK v2' abliteration — tuned for conversational vision inputs and thinking-mode support in JANG v2 safetensors format. Recommended to run in vMLX; published by dealignai.
AI Model2026
Generates persistent, explorable 3D worlds from a single image by synthesizing long-range, geometry-consistent video and reconstructing it into an explicit 3D Gaussian scene. Intended for internal research use under NVIDIA's research license.
AI Model2026
An 8B-parameter, instruction-tuned long-context LLM optimized for instruction following, tool-calling, and multilingual dialogue — supports 131072-token context and common NLP tasks such as summarization, QA, code, and RAG.
AI Model2026
A 30B-parameter, instruction-tuned language model built for long-context text generation, conversational agents, and tool-calling. It combines supervised fine-tuning and RL alignment, supports 131,072-token context, and is optimized for tasks like summarization, code, and RAG.
AI Model2026
An open text-to-image generation model built on an 8B Diffusion Transformer that focuses on layout-sensitive, text-heavy, and instruction-following image synthesis. Notable for accurate text rendering, structured/compositional generation (posters, comics), and ability to run on consumer 24GB GPUs when paired with prompt enhancement.
AI Dataset2026
Provides 12.26M synthetically generated multilingual OCR samples (en/ja/ko/ru/zh) with word/line/paragraph bounding boxes and reading-order graphs, packaged as HDF5 shards for training detection, recognition, and layout models; licensed CC BY 4.0.
AI Dataset2026
Benchmarks document-parsing systems on real-world enterprise PDFs and images—evaluates tables, charts, content faithfulness, semantic formatting, and visual grounding with human-verified, rule-level tests. Ships with ~2,000 pages, ~169K test rules, and an open evaluation framework for end-to-end pipeline scoring.
AI Model2026
Text-generation LLM designed for agentic workflows: supports multi-agent 'Agent Teams', skill stacks and model self-evolution. Ships on Hugging Face with deployment guides (vLLM, Transformers, SGLang) and is positioned for engineering, tool-calling and productivity use cases.
AI Model2026
Generates and reconstructs navigable, editable 3D worlds from text, single images, multi-view photos, or video; outputs meshes and Gaussian Splatting assets and includes WorldMirror 2.0 for fast multi-view reconstruction. Suited for research and production pipelines that import assets into engines; requires substantial GPU resources.
AI Model2026
Generates text by iteratively denoising blocks of tokens with a two-tower design: a frozen autoregressive context tower and a trainable diffusion denoiser tower, trading minimal quality loss for higher wall-clock throughput.
AI Dataset2026
Provides one million executable, human-readable CadQuery construction sequences synthesized by an LLM-in-the-loop—each sample includes renders, STL/STEP exports, precomputed DINOv3 embeddings and a FAISS index. Designed for training and benchmarking text/image→3D and CAD-program generation models (Apache-2.0).