AI Model2026
Provides GGUF-quantized weights and runtime assets for running the Qwythos-9B reasoning LLM locally via llama.cpp and compatible runtimes. Key features include 1,048,576-token YaRN long-context, native function-calling, multimodal image input (requires mmproj), and multiple quantization/MTP variants tuned for different size/quality tradeoffs.
AI Dataset2026
Zeren Jiang, Yushi Lan +9Visual Geometry Group, University of Oxford, Nanyang Technological University +1
Provides multiview synthetic RGB video clips with per-frame depth, instance masks, dense long-range 3D point tracks, camera poses, and SMPL‑X human pose/shape labels for 4D reconstruction, tracking, and geometry-aware novel-view synthesis. Includes ~4.7K clips (1.4M frames) and is licensed for AI training.
AI Dataset2026
Provides ~2 million instruction-aligned video-edit pairs for training and evaluating instruction-based video editing and generation models. Covers multi-task and structural edits (e.g., camera/subject movement), produced via a synthesis pipeline with progressive filtering; licensed CC BY-NC-4.0.
AI Dataset2026
Multimodal video dataset for text-to-video and video-to-video research: about 2 million short English videos and extracted frames for instruction-based video editing and generation. Hosted on Hugging Face and licensed CC BY‑NC 4.0 (non-commercial).
AI Model2026
NVFP4-quantized variant of Qwen3.6-27B that reduces parameter bits from 16 to 4, cutting disk and GPU memory requirements by ~2.5× while keeping comparable benchmark accuracy; ready for vLLM-based inference on NVIDIA hardware and supports long, multimodal contexts.
Provides a rubric-based benchmark that converts dense image captions into instance-specific atomic checks (Must-Right and Easy-Wrong) and a gated scoring rule, aiming to expose perceptual brittleness and better align multimodal model evaluation with human judgment.
AI Dataset2026
Provides synchronized four-perspective Rocket League match recordings with per-frame H.264 video, player action streams, event logs, and privileged physics state — released as WebDataset shards in a ~4,000-hour slice (1,000 match-hours × 4 perspectives). Includes 720p@20fps video, multi-hot keyboard actions, and CC BY-NC-SA-4.0 license.
AI Model2026
Thinking-off fine-tune for coding-agent workflows that prioritizes fast next-step decisions, lower token usage and stable multi-turn tool calling. Highlights: MoE 35B base, MTP speculative decoding, SWE-bench 62.4% (300 cases). Best for local agent loops and automated debug cycles; requires disciplined harnessing and schema consistency.
AI Dataset2026
Provides ~494.7 hours of trimmed native PC/console gameplay screen recordings organized by game, with per-session clips plus input and per-frame event annotations. Each workflow includes clip.mp4, events.json, frame_events.json, and metadata — suitable for training vision-action, behavior-cloning, and gameplay understanding models.
AI Dataset2026
Provides ~50M multimodal annotations organized for unified training across structured visual understanding, segmentation, dense geometric prediction, and multi-view reconstruction — released as task-specific JSONL files that reference original image assets rather than redistributing raw images.
AI Model2026
Provides GGUF/llama.cpp quantized variants of Qwen3.6-27B for local multimodal inference, tuned via online RL to cut average 'thinking' tokens by ≈50% while preserving answer quality; offers Q4_K_M/Q8_0/f16 builds and a separate mmproj for vision input.
AI Model2026
Provides quantized GGUF weights and configs for Agents‑A1 — a 35B Mixture-of-Experts agent trained for long-horizon, tool-enabled reasoning; supports 262K-context serving and runtimes like vLLM and SGLang.