🔴 Advanced ⚙️ Type: Long-Form AI Video & Audio Generation 💸 Free & Open Source ⭐ Trending on GitHub
What is JoyAI-Echo?
JoyAI-Echo (also known as Echo-LongVideo) is a revolutionary open-source AI model released by JD.com’s Echo Team at the Joy Future Academy. It was built to solve the biggest frustration in generative AI video: the inability to tell a coherent story.
Most open-source video models produce visually stunning but completely disconnected 5-second clips. JoyAI-Echo shatters this limitation by generating up to 5-minute-long, multi-shot narratives. Furthermore, it doesn’t just generate silent pixels; it simultaneously generates the video, the character’s spoken dialogue, sound effects, and background music in a single, unified pass.
Built upon the LTX-Video backbone and powered by the massive Gemma 3 (12B) text encoder, JoyAI-Echo introduces a Cross-Modal Audio-Visual Memory Bank. This memory system allows the AI to “remember” exactly what a character looks and sounds like in shot 1, ensuring their face, clothing, and voice timbre remain perfectly consistent in shot 15, even as the camera angles and environments change.
Who is it for?
- Filmmakers and Content Creators who want to generate complete, narrative-driven short films without the nightmare of stitching together hundreds of inconsistent, random AI clips.
- Game Developers and Animators looking to prototype long cutscenes with consistent characters, dynamic camera movements, and synced audio.
- Marketing and Ad Agencies automating the creation of digital spokesperson videos where the brand’s virtual actor needs to maintain a stable face and voice across multiple scenes.
- AI Researchers experimenting with state-of-the-art Distribution Matching Distillation (DMD) and multi-modal memory architectures.
What makes it special?
- Audio-Visual Memory Bank — The holy grail of AI video. The model actively tracks character traits across scenes. If a character speaks in a deep voice while wearing a red jacket in the opening scene, the model enforces that exact look and sound throughout the entire 5-minute video.
- Native Multi-Modal Output — You no longer need separate subscriptions to Midjourney, Runway, ElevenLabs, and Suno. JoyAI-Echo generates the environment, the character, their speech, and the background music all at once, ensuring perfect lip-sync and audio-visual timing.
- DMD Acceleration — Through a specialized Distribution Matching Distillation (DMD) post-training pipeline, JD.com managed to increase the model’s inference speed by 7.5x compared to standard diffusion models, without sacrificing visual quality.
- Director Agent Workflow — It supports a “conversational editing” pipeline. You can chat with the AI to refine your script into structured JSON shot-lists before rendering, acting like a true virtual director.
Requirements before you start
Because JoyAI-Echo pushes the absolute limits of current open-source generative AI, the hardware requirements are strictly enterprise-grade:
- Massive GPU VRAM — At default settings (1280×736 at 25 FPS), the model requires 46 GB to 50 GB of VRAM. You will need an NVIDIA A100 (80GB), H100, or RTX 6000 Ada. (Future community updates via ComfyUI may optimize this for 24GB consumer cards, but the official pipeline requires heavy compute).
- Linux Operating System — Ubuntu or WSL2 on Windows is highly recommended for PyTorch compilation.
- Storage Space — You need at least 80 GB of free NVMe SSD space to hold the 46GB main model and the 24GB Gemma-3 text encoder.
- FFmpeg — Required for concatenating the multi-shot audio and video chunks into the final MP4 file.
Step-by-step installation
Step 1 — Clone the Repository
Open your terminal and pull the official code from JD.com’s repository:
git clone https://github.com/jd-opensource/JoyAI-Echo.git
cd JoyAI-EchoStep 2 — Create the Python Environment
The developers recommend Python 3.11 with PyTorch 2.8 and CUDA 12.8. Use Conda to set up your isolated environment automatically:
conda env create -f environment.yml
conda activate echo-long(Ensure FFmpeg is installed on your system: sudo apt install ffmpeg)
Step 3 — Download the Model Weights
You need to download the main JoyAI-Echo `.safetensors` file and the Gemma 3 (12B) text encoder. Create a folder named checkpoints/ in your project directory and arrange them like this:
checkpoints/
├── echo-longvideo-release.safetensors
└── gemma-3-12b/Step 4 — Prepare Your Story Prompt
JoyAI-Echo requires structured prompts. Inside the prompts/ folder, create a JSON file where each string represents a sequential camera shot. The model reads this list and uses its memory bank to connect them.
Tip: Run your basic idea through the provided prompts/long_story_writer_system_prompt.md using an LLM first to get perfectly formatted character, dialogue, and camera movement instructions.
Step 5 — Run Inference
Execute the official inference script. The system will load the models, process all JSON files in your prompts folder, and output the final video:
python inference.pyYour multi-shot, audio-synced cinematic masterpiece will be saved in the inference_result/outputs/ directory!
Common errors and fixes
| Error | What it means | How to fix it |
|---|---|---|
CUDA Out of Memory (OOM) | Your GPU has less than 46GB of VRAM, and the massive audio-video memory mechanism cannot fit alongside the 12B parameter text encoder. | Wait for the community to release heavily quantized versions (like GGUF or NF4) for ComfyUI, or rent a cloud GPU instance (like an A100) via RunPod or Lambda Labs to run the official script. |
FFmpeg is not recognized as an internal or external command | The model finished generating the individual shots but failed to stitch the video and audio streams together. | Install FFmpeg on your host OS and ensure its bin/ folder is added to your system’s PATH environment variable. |
| Characters morph or change clothes between scenes | Your text prompts are too vague, causing the model’s memory bank to lose tracking continuity. | Always use the provided prompt enhancers. You must explicitly describe the character’s core features (age, clothes, voice) consistently in the structured JSON array for the memory module to lock onto them. |
Free vs Paid comparison
| Feature | JoyAI-Echo (Open Source) | Commercial Leaders (Sora / Veo / Gen-3) |
|---|---|---|
| Cost | $0 (Requires heavy hardware) | $20 to $100+ per month subscription |
| Video Length Limits | ✅ Up to 5 minutes (multi-shot) | Usually capped at 5 to 10 seconds |
| Character & Voice Consistency | ✅ Excellent (Native Cross-Modal Memory) | ❌ Poor (Requires heavy manual post-editing) |
| Hardware Required | ❌ Extreme (46GB+ VRAM) | 🟢 Minimal (Web browser) |
Bottom line: JoyAI-Echo is a massive leap forward, signaling the end of the “AI slot machine” era where creators had to roll the dice hundreds of times to get consistent scenes. Its ability to generate minutes of cohesive video and synced audio is unmatched in the open-source world. However, the staggering 46GB VRAM requirement means standard consumers will have to rent cloud GPUs to use it until the community optimizes it for smaller cards.
Alternatives — 3 similar tools
1. Wan 2.6
Another titan of the open-source video generation space. While Wan 2.6 often produces slightly higher aesthetic fidelity and physics simulation in single, isolated clips, it lacks JoyAI-Echo’s multi-shot memory bank and native audio integration, making it worse for long-form storytelling.
🔗 github.com/Wan-Video/Wan (Base repository)
2. LTX-Video
The core backbone that JoyAI-Echo was built upon. Lightricks’ LTX-Video is incredibly fast and produces excellent high-resolution footage. If you don’t care about audio generation or multi-shot character memory and just want to generate fast 5-second B-roll clips, running base LTX-Video is much lighter on your hardware.
🔗 github.com/Lightricks/LTX-Video
3. Luma Dream Machine
If you don’t have the enterprise hardware required to run JoyAI-Echo locally, Luma Dream Machine is a fantastic commercial cloud alternative. It excels at fast, high-quality video generation through a simple web interface, though you will still struggle to maintain perfect character consistency across long timelines without post-production work.
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