Total runs:
36.1K
Run Growth:
36.1K
Growth Rate:
100.00%
Sponsored by
APIMart
chfm / JoyAI-Echo_GGUF
Model's Last Updated: June 09 2026
Introduction of JoyAI-Echo_GGUF
Model Details of JoyAI-Echo_GGUF
JoyAI-Echo — GGUF (for low-VRAM ComfyUI)
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
⚠️ 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_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.)
Not included: the text encoder
JoyAI-Echo uses
Gemma-3-12B
as its text encoder. It isn't rehosted here — download
gemma_3_12B_it_fp8_scaled.safetensors
(Comfy-Org from
google/gemma-3-12b-it
.
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
- Install the ComfyUI nodes .
-
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). -
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
- JoyAI-Echo — Echo Team @ Joy Future Academy, JD
- LTX-2.3 — Lightricks
- Gemma-3 — Google
- GGUF tooling: city96/ComfyUI-GGUF
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.
Runs of chfm JoyAI-Echo_GGUF on huggingface.co
15
Total runs
0
24-hour runs
-2
3-day runs
-2
7-day runs
8
30-day runs
More Information About JoyAI-Echo_GGUF huggingface.co Model
Url of JoyAI-Echo_GGUF
JoyAI-Echo_GGUF huggingface.co Url
Provider of JoyAI-Echo_GGUF huggingface.co
Other API from chfm
Updated:September 21 2026
Total runs:
7.7K
Run Growth:
7.7K
Growth Rate:
100.00%
Total runs:
5.1K
Run Growth:
5.1K
Growth Rate:
100.00%
Total runs:
2.8K
Run Growth:
1.8K
Growth Rate:
61.90%
Total runs:
2.3K
Run Growth:
2.0K
Growth Rate:
88.77%
Total runs:
1.9K
Run Growth:
1.9K
Growth Rate:
100.00%
Total runs:
1.9K
Run Growth:
-112
Growth Rate:
-5.91%
Total runs:
1.8K
Run Growth:
1.8K
Growth Rate:
96.73%
Total runs:
1.2K
Run Growth:
-3.7K
Growth Rate:
-306.49%
Total runs:
1.2K
Run Growth:
-531
Growth Rate:
-44.29%
Total runs:
1.0K
Run Growth:
805
Growth Rate:
77.03%
Total runs:
762
Run Growth:
354
Growth Rate:
46.46%
Total runs:
574
Run Growth:
82
Growth Rate:
14.29%
Total runs:
571
Run Growth:
166
Growth Rate:
29.07%
Total runs:
387
Run Growth:
298
Growth Rate:
77.00%
Total runs:
358
Run Growth:
-202
Growth Rate:
-56.42%
Total runs:
278
Run Growth:
51
Growth Rate:
18.35%
Total runs:
221
Run Growth:
221
Growth Rate:
100.00%
Total runs:
202
Run Growth:
-12
Growth Rate:
-5.94%
Total runs:
184
Run Growth:
-32
Growth Rate:
-17.39%
Total runs:
162
Run Growth:
-4
Growth Rate:
-2.47%
Total runs:
138
Run Growth:
-44
Growth Rate:
-31.88%
Total runs:
121
Run Growth:
-276
Growth Rate:
-228.10%
Total runs:
120
Run Growth:
-78
Growth Rate:
-65.00%
Total runs:
67
Run Growth:
38
Growth Rate:
56.72%
Total runs:
64
Run Growth:
-482
Growth Rate:
-753.13%
Total runs:
56
Run Growth:
-123
Growth Rate:
-219.64%
Total runs:
56
Run Growth:
-34
Growth Rate:
-60.71%
Total runs:
47
Run Growth:
-33
Growth Rate:
-70.21%
Total runs:
46
Run Growth:
-43
Growth Rate:
-93.48%
Total runs:
22
Run Growth:
-20
Growth Rate:
-90.91%
Total runs:
20
Run Growth:
2
Growth Rate:
10.00%
Total runs:
19
Run Growth:
-4
Growth Rate:
-21.05%
Total runs:
17
Run Growth:
-74
Growth Rate:
-435.29%
Total runs:
13
Run Growth:
-8
Growth Rate:
-61.54%
Total runs:
11
Run Growth:
-11
Growth Rate:
-100.00%
Total runs:
11
Run Growth:
2
Growth Rate:
18.18%
Total runs:
7
Run Growth:
-3
Growth Rate:
-42.86%
Total runs:
6
Run Growth:
2
Growth Rate:
33.33%
Total runs:
0
Run Growth:
0
Growth Rate:
0.00%
Total runs:
0
Run Growth:
0
Growth Rate:
0.00%
Total runs:
0
Run Growth:
0
Growth Rate:
0.00%
Total runs:
0
Run Growth:
0
Growth Rate:
0.00%
Total runs:
0
Run Growth:
0
Growth Rate:
0.00%
Total runs:
0
Run Growth:
0
Growth Rate:
0.00%
Total runs:
0
Run Growth:
0
Growth Rate:
0.00%
Total runs:
0
Run Growth:
0
Growth Rate:
0.00%
Total runs:
0
Run Growth:
0
Growth Rate:
0.00%