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JoyAI Echo GGUF

Quantized GGUF weights and extracted components for running JD's JoyAI-Echo — a text → video + audio model — on consumer GPUs.

Sourcehuggingface.co/realrebelai/JoyAI-Echo_GGUF/tree/e3c0bff88ada1b6b45a1814e8493de67baa5d936
KindUNetBase modeljdopensource/JoyAI-EchoVersionjoyai_echo_embeddings_processorBgrade

Model source

Kind
UNet
File size
5.91 GB
Base model
jdopensource/JoyAI-Echo
Version
vjoyai_echo_embeddings_processor
Updated
Oct 27, 2026
Downloads
822
Source
Hugging Face

Source description

JoyAI-Echo — GGUF (for low-VRAM ComfyUI)

Screenshot (160)

Quantized GGUF weights and extracted components for running JD's JoyAI-Echo — a text → video + audio model — on consumer GPUs.

The original release is a single ~46 GB bf16 checkpoint built for ~48 GB-class hardware. These files let it run on 8 GB VRAM + 16 GB RAM through the companion ComfyUI nodes.

▶ Nodes / how to run: https://github.com/RealRebelAI/ComfyUI_JoyAI_Echo_GGUF_Nodes

▶ (Optional) Colorful Int Nodes: https://github.com/RealRebelAI/Rebels_Better_Int_Node

▶ (Optional) Animated Nodes: https://github.com/RealRebelAI/Rebels_Animated_Nodes

⚠️ Experimental. These run, but on small hardware loads and the first encode are slow. See the node repo for expectations and troubleshooting.

What's in this repo

FileWhat it isNotes
JoyAI-Echo-DiT-Q2_K.ggufDiffusion transformer, Q2_KSmallest / lowest RAM. Start here on 8 GB.
JoyAI-Echo-DiT-Q4_K_M.ggufDiffusion transformer, Q4_K_MHigher quality, more RAM.
JoyAI-Echo-DiT-Q4_K_M_RM.ggufDiffusion transformer, REBEL MIX PRECISION GGUFexperimental precision layering technique is used to yield higher quality outputs from quantization.
JoyAI-Echo-DiT-Q6_K_RM.ggufDiffusion transformer, REBEL MIX PRECISION GGUFexperimental precision layering technique is used to yield higher quality outputs from quantization. (Larger size)
joyai_echo_video_vae.safetensorsVideo VAERequired.
joyai_echo_audio_vae.safetensorsAudio VAERequired.
joyai_echo_vocoder.safetensorsVocoderRequired for audio.
joyai_echo_embeddings_processor.safetensorsText-embedding connectorRequired.
joyai_echo_config.jsonArchitecture configAlso ships inside the node pack.

(Sizes are approximate; check the file listing. Q2_K is the lighter option, Q4_K_M the heavier/higher-quality one.)

Why GGUF (and why these specific files)

Stock ComfyUI GGUF loaders build the wrong architecture for JoyAI-Echo — it's a modified LTX-2.3 (different scale_shift_table and connector dimensions). The companion nodes rebuild it correctly with JoyAI's own configurator and keep the DiT weights packed in GGUF form, dequantizing on the fly so the model fits in limited RAM/VRAM.

The VAEs, vocoder, and connector are extracted from the original checkpoint as standalone files so you don't need the 46 GB bundle at runtime.

Usage

  1. Install the ComfyUI nodes.
  2. Download the files above and place them in the ComfyUI folders listed in the node README (models/unet, models/vae, models/audio_encoders, models/text_encoders).
  3. Add the RebelsJE_StagedPipeline node → CreateVideo → SaveVideo, pick the files from the dropdowns, prompt, and queue.

Pick Q2_K first if you're on 8 GB; move up to Q4_K_M if you have RAM headroom and want better quality.

Hardware

  • Minimum target: 8 GB VRAM + 16 GB RAM (RTX 3070 class).
  • SSD strongly recommended — the files load much faster than from a spinning disk.

Acknowledgements

License

These quantized weights are derived from JoyAI-Echo and are released for academic research and non-commercial use only, following the upstream JoyAI-Echo license. Gemma components (downloaded separately) are governed by Google's Gemma license. By downloading you agree to those terms.

Sources

1 source
Hugging FacePrimaryVersion e3c0bff88ada1b6b45a1814e8493de67baa5d936
huggingface.co/realrebelai/JoyAI-Echo_GGUF/tree/e3c0bff88ada1b6b45a1814e8493de67baa5d936

Verified Oct 27

Model artifacts

1 artifact

joyai_echo_embeddings_processor.safetensors

safetensors · 5.91 GB · SHA-256 6f28086142c4…c9e5 · Hugging Face

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Source excerpts

3 excerpts
ReadmeAug 8huggingface.co/realrebelai/JoyAI-Echo_GGUF

--- base_model: jdopensource/JoyAI-Echo tags: - gguf - text-to-video --- - # JoyAI-Echo — GGUF (for low-VRAM ComfyUI) ![Screenshot (160)](https://cdn-uploads.huggingface.co/production/uploads/68761990332d15464ccc8dee/R7OzYqiC_z7bquiQ2tD2W.png) Quantized **GGUF** weights and extracted components for running JD's [JoyAI-Echo](https://github.com/jd-opensource/JoyAI-Echo) — a text → **video + audio** model — on consumer GPUs. The original release is a single ~46 GB bf16 checkpoint built for ~48 GB-class hardware. These files let it run on **8 GB VRAM + 16 GB RAM** through the companion ComfyUI nodes. **▶ Nodes / how to run:** https://github.com/RealRebelAI/ComfyUI_JoyAI_Echo_GGUF_Nodes **▶ (Optional) Colorful Int Nodes:** https://github.com/RealRebelAI/Rebels_Better_Int_Node **▶ (Optional) Animated Nodes:** https://github.com/RealRebelAI/Rebels_Animated_Nodes > ⚠️ Experimental. These run, but on small hardware loads and the first encode are slow. See the node repo for expectations and troubleshooting. --- ## What's in this repo | File | What it is | Notes | |------|------------|-------| | `JoyAI-Echo-DiT-Q2_K.gguf` | Diffusion transformer, Q2_K | Smallest / lowest RAM. Start here on 8 GB. | | `JoyAI-Echo-DiT-Q4_K_M.gguf` | Diffusion transformer, Q4_K_M | Higher quality, more RAM. | | `JoyAI-Echo-DiT-Q4_K_M_RM.gguf` | Diffusion transformer, REBEL MIX PRECISION GGUF| experimental precision layering technique is used to yield higher quality outputs from quantization. | | `JoyAI-Echo-DiT-Q6_K_RM.gguf` | Diffusion transformer, REBEL MIX PRECISION GGUF| experimental precision layering technique is used to yield higher quality outputs from quantization. (Larger size) | | `joyai_echo_video_vae.safetensors` | Video VAE | Required. | | `joyai_echo_audio_vae.safetensors` | Audio VAE | Required. | | `joyai_echo_vocoder.safetensors` | Vocoder | Required for audio. | | `joyai_echo_embeddings_processor.safetensors` | Text-embedding connector | Required. | | `joyai_echo_config.json` | Architecture config | Also ships inside the node pack. | *(Sizes are approximate; check the file listing. Q2_K is the lighter option, Q4_K_M the heavier/higher-quality one.)* ## Why GGUF (and why these specific files) Stock ComfyUI GGUF loaders build the **wrong architecture** for JoyAI-Echo — it's a *modified* LTX-2.3 (different `scale_shift_table` and connector dimensions). The c...

NoteOct 27huggingface.co/realrebelai/JoyAI-Echo_GGUF

Source context: 822 downloads · 17 likes · Pipeline text-to-video · Repo realrebelai/JoyAI-Echo_GGUF

NoteAug 8huggingface.co/realrebelai/JoyAI-Echo_GGUF

Source context: 1753 downloads · 13 likes · Pipeline text-to-video · Repo realrebelai/JoyAI-Echo_GGUF