gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors
Gemma 4 12B with Projection INT8 convrot (Text Encoder)
Official INT8 quantized Gemma 4 12B text encoder for LTX 2.5, projection bundled in. This is the smallest official text encoder — at 15.37GB it's already larger than LTX 2.3's smallest encoder (9.5GB), which is why 16GB cards can't run an all-official LTX 2.5 pipeline. Place in models/text_encoders/. Repo is gated.
Download gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors
Official HuggingFace repo — sign in and click "Agree and Access" to accept the LTX 2.5 license before this downloads. 15.37 GB · Free.
No 16GB GPU? Try gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors online — free generation included
Skip the 15.37 GB download and ComfyUI setup. Generate a 6-second video using this exact model in your browser, ~30 seconds.
When to choose gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors
Required alongside any official 2.5 transformer. If you're targeting 16GB total, this file alone plus the smallest official transformer (21.50GB) won't fit — use the GGUF Gemma 4 encoder (9.51GB) instead.
Will this run on my GPU?
Minimum: 16GB VRAM.
How to use gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors
- Download the file from HuggingFace.
- Place it in ComfyUI/models/text_encoders/ inside your ComfyUI directory.
- Restart ComfyUI (or refresh the model list from the menu).
- Load a compatible workflow — see below.
See the LTX 2.5 ComfyUI setup guide for the full file list and install order.
Don't want to run this locally? Try gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors online with a free generation — no GPU, no install, ~30 seconds per clip.
ComfyUI says it can't find gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors?
Some published workflow JSONs reference this file under a custom subdirectory. If ComfyUI shows a "cannot find model" error and your workflow references one of these path-prefixed variants:
- text_encoders/gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors
The prefix before the slash or backslash is a subdirectory the workflow author used. The actual file is the same gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors — you have two fixes:
- Create the matching subdirectory inside ComfyUI/models/text_encoders/ and place the file there. Example: if the workflow references text_encoders/gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors, create the corresponding subfolder under ComfyUI/models/text_encoders/ and put gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors inside it.
- Or open the workflow JSON in a text editor and replace the prefixed string with just gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors. ComfyUI then resolves it directly from ComfyUI/models/text_encoders/.
On Windows the separator is \, on macOS/Linux it is / — they refer to the same nested folder regardless of platform.
Common issues
ComfyUI doesn't see the file after I downloaded it▼
Make sure the file is in ComfyUI/models/text_encoders/ (not a subfolder). Restart ComfyUI fully — the menu refresh sometimes misses new files. Filename must match exactly: gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors.
CUDA out of memory error when loading the model▼
gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors needs ~16GB VRAM minimum. If you're hitting OOM: • Enable Sequential Offloading in ComfyUI settings • Lower the resolution (768×512 instead of 1280×704) — both dimensions must be divisible by 32 • Reduce frame count (65 frames instead of 161) — must be 8n+1 • Use a smaller variant — see Related models below.
How do I apply this LoRA in ComfyUI?▼
Load it in a 'LoraLoader' node and connect it after your model loader. Pair this LoRA with the dev base model (not the distilled one) for the right behavior. LoRA strength 1.0 is the trained value — start there.
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