AI Model2026
Unifies multimodal understanding, reasoning, and image generation in a single end-to-end architecture using the NEO-unify paradigm. Models pixels and words jointly without a separate visual encoder, and provides interleaved image–text generation, infographic editing, and GGUF/low‑VRAM inference options.
AI Model2026
Diffusion-based generative model for scene and video synthesis, providing full Diffusers checkpoints and scene LoRA for fast adaptation. Includes Stage‑1 nano (1.3B) and pro (5B) variants and modular transformer/VAE components.
AI Model2026
Depth-conditioned LoRA for Krea‑2 that extracts a depth map from any input image and generates new images preserving the original 3D structure and composition while changing content and style. Single 862MB LoRA, works with Krea‑2‑Raw and Krea‑2‑Turbo.
AI Video2026
Generates short videos that preserve a reference person's identity from a single reference image as a LoRA adapter for LTX-2. Uses overlap reference conditioning with TASS‑RoPE source-phase tagging and an ArcFace identity loss; runs in ComfyUI via BFS Nodes and supports a 4‑panel character‑sheet mode for clothing/body consistency.
AI Model2026
Enhances KREA-2 Turbo image generations with an aesthetic LoRA trained on a curated 100-image dataset to add stronger composition, richer lighting, softer atmosphere and refined textures; trigger with --preview for art-directed, cinematic outputs in text-to-image pipelines.
AI Video2026
Generates videos from text and image+text prompts using a 30B Mixture-of-Experts model tuned for embodied intelligence; includes a refiner and structured prompt rewriter, and supports diffusers/SGLang runtimes with multi-GPU inference.
AI Model2026
A 9B-parameter Qwen3.5-based multimodal model tuned to preserve chain-of-thought reasoning while eliminating repetition loops; restores native multi-token prediction, supports 1,048,576-token context, and targets research/red-team use.
AI Video2026
Generates a new camera viewpoint from a reference video: an IC‑LoRA adapter for LTX‑Video 2.3 that re‑renders the same scene from a requested discrete camera angle while preserving subject and content. Trained on synthetic multi‑view data, proof‑of‑concept with limited viewpoint range and best for small, chained angle shifts.