Model reference · open weights
JoyAI-Video-Ed is an open-weight video model from jdopensource, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.
About
Real-Time Open-Ended Video Editing with Autoregressive Diffusion src="https://raw.githubusercontent.com/jd-opensource/JoyAI-Video-Edit/main/assets/teaser.jpg" width="96%" alt="JoyAI-Video-Edit teaser" 🐶 JoyAI-Video-Edit JoyAI-Video-Edit is a real-time, instruction-guided video editing system for open-ended video streams. Given a live camera stream or uploaded video and a natural-language edit instruction, it edits frames causally as they arrive, without waiting for the full video, requiring a predefined video length, or revisiting future frames. In our deployment benchmark, the full end-to-end pipeline reaches 30 FPS at 720 × 1248, pushing video editing from offline batch processing toward interactive streaming generation. The system combines an MLLM-based condition encoder, a causal video VAE, and a 16B-parameter multimodal diffusion transformer. It is trained and deployed as an autoregressive diffusion editor, then accelerated with aligned autoregressive distribution matching distillation, long-horizon optimization, bounded KV-state inference, and deployment-oriented scheduling to sustain high-throughput 720p editing while reducing train-inference mismatch and accumulated temporal drift. 🔥 News - 2026.08.24 — 🎉 Consumer GPU support landed: real-time streaming video editing on a single GeForce RTX 5090 (32 GB) at 840 × 480 @ 24 FPS. Deployment Guide - 2026.08.15 — 🎉 Live demo released — real-time streaming video editing on a single RTX PRO 6000 (Blackwell) GPU: 840 × 480 @ 24 FPS or 720p @ 16 FPS. Try HuggingFace Demo - 2026.08.14 — 🎉 Released an upgraded checkpoint with significantly stronger reference-image-guided video editing (RV2V), delivering better subject and identity preservation, more faithful reference conditioning, and improved temporal consistency across long streams. Grab the new DiT weights. - 2026.08.05 — 🎉 We released the model checkpoints, deployment code, and technical report. 💎 Highlights - Real-time open-ended editing. Edits live or uploaded videos as frames arrive, without requiring the full sequence upfront. - Diverse instruction control. Supports subject edits, local edits, background changes, style transfer, motion changes, and referenc
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | jdopensource |
|---|---|
| Type | Video models |
| Variants | 1 |
| Runs with | joyai-video-edit |
| Released | 2026-08-04 |
| Popularity | 4k downloads / month |
| Likes | 96 |
| Licence | Open weights |
How it works
Variants
Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.
| Variant | Params | Precision | VRAM | Fits 16 GB | Weights |
|---|---|---|---|---|---|
| JoyAI-Video-Edit | — | BF16 | — | — | Weights ↗ |
Using it via the API
Once AxForge deploys joyai-video-ed for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (joyai-video-ed below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/videos/generations \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"joyai-video-ed","prompt":"a drone shot over a forest"}'
Licence
Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗
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