Krea RealTime Video 14B FP8 - The Ultra-Efficient, almost Real-Time Video Generator! 🚀

Introducing the highly anticipated FP8 Quantized version of Krea RealTime 14B - a groundbreaking 14-billion parameter model that delivers true real-time, long-form video generation with unprecedented VRAM efficiency. This model is specially optimized for maximum performance and a dramatically reduced memory footprint, making the cutting edge of interactive AI video accessible on a wider range of modern consumer and enterprise GPUs. Get ready for immense power and efficiency! 💡🔋

If this FP8 version is too big for your VRAM then maybe this Workflow for GGUF (get yourself Q-4-M WAN2.1) + Krea LORA is here: https://civarchive.com/models/2065245?modelVersionId=2336991 will be helpful for you ;)

Also here is the cmd-line that helps to generate more frames per one run: ".\python_embeded\python.exe -s ComfyUI\main.py --windows-standalone-build --disable-xformers --use-pytorch-cross-attention --dont-upcast-attention --fp8_e4m3fn-unet --fp8_e4m3fn-text-enc --disable-api-nodes --lowvram
pause"

The original Krea RealTime 14B model moves beyond static, "one-shot" video generation. It's built for a fluid, creative workflow with true real-time streaming, allowing users to see the first frames in as little as 1 second. The real magic is its Real-Time Steerability: users can change prompts, modify styles, and inject new elements mid-generation, effectively directing the video as it's being created. This offers a level of control never before seen in large-scale models. 🎨🎬

At its core, Krea RealTime 14B is an autoregressive powerhouse with 14 billion parameters - over 10x larger than previous open-source real-time models. This scale results in superior high-frequency detail and better modeling of complex, dynamic movements. The model was distilled from the powerful Wan 2.1 14B teacher model using the Self-Forcing technique. This innovative process trains the model on its own imperfect outputs, virtually eliminating the catastrophic exposure bias errors that plague other autoregressive methods and guaranteeing stability. ✅

To ensure stable, long-form video, the original developers engineered a suite of novel inference techniques. Solutions like KV Cache Recomputation and Dynamic KV Cache Management solve the challenges of extended generation, allowing the model to produce coherent, stable sequences far beyond typical limits. Download this FP8 checkpoint to experience the future of interactive, steerable video generation on your hardware with maximum efficiency! ⬇️💾