---
title: LTX-2.5_GGUFs
canonical_url: "https://www.modelscope.ai/models/RealRebelAi/LTX-2.5_GGUFs"
md_url: "https://www.modelscope.ai/models/RealRebelAi/LTX-2.5_GGUFs.md"
repository: RealRebelAi/LTX-2.5_GGUFs
last_updated: 2026-08-14
license: other
pipeline_tag: text-to-video-synthesis
tasks:
  - text-to-video-synthesis
base_model:
  - Lightricks/LTX-2.5
base_model_relation: quantized
library_name:
  - gguf
  - pytorch
frameworks:
  - pytorch
downloads: 172
stars: 0
tags:
  - gguf
  - quantized
  - comfyui
  - ltx
  - ltxv
  - text-to-video
  - image-to-video
  - audio-video
  - low-vram
---

# LTX-2.5_GGUFs

> LTX-2.5_GGUFs - An open-source model by RealRebelAi on ModelScope. GGUF quantizations of Lightricks' LTX-2.5, converted for ComfyUI with ComfyUI-GGUF.

RealRebelAi/LTX-2.5_GGUFs is a text-to-video-synthesis model on ModelScope. licensed under other. derived from Lightricks/LTX-2.5.

- **Repository**: RealRebelAi/LTX-2.5_GGUFs
- **License**: other
- **Tasks**: text-to-video-synthesis
- **Base model**: Lightricks/LTX-2.5
- **Tags**: gguf, quantized, comfyui, ltx, ltxv, text-to-video, image-to-video, audio-video, low-vram
- **Downloads**: 172
- **Stars**: 0
- **Last updated**: 2026-08-14

Source: https://www.modelscope.ai/models/RealRebelAi/LTX-2.5_GGUFs

---

# LTX-2.5 22B — GGUF

GGUF quantizations of Lightricks' LTX-2.5, converted for ComfyUI with [ComfyUI-GGUF](https://github.com/city96/ComfyUI-GGUF).

LTX-2.5 generates **video and synchronized audio in a single pass** — a dual-stream DiT with a 4096-wide video path, a 2048-wide audio path, and cross-modal attention joining them. The bf16 transformer is 39 GB. These quants bring it to 8-22 GB.

All original licensing terms and usage restrictions carry over from the base model.

---

## The config metadata problem

**If you convert LTX-2.5 to GGUF yourself, it will not load.** These files have the fix baked in; this section explains what it is, because it isn't obvious and it cost a night to find.

ComfyUI derives most model dimensions from tensor shapes. For LTX-2.5 it can't: the connector widths, the audio path dimension, and the 9-row modulation tables are only knowable from a `config` blob stored in the original safetensors `__metadata__`. ComfyUI reads it here:

```python
dit_config.update(json.loads(metadata["config"]).get("transformer", {}))
```

GGUF has no `__metadata__` field, so every standard conversion drops it. ComfyUI then builds an LTX-**2.3**-shaped model and pours 2.5 weights into it, producing a wall of shape mismatches:

```
size mismatch for audio_embeddings_connector.learnable_registers:
  copying a param with shape torch.Size([128, 2048]) from checkpoint,
  the shape in current model is torch.Size([128, 3840])
size mismatch for transformer_blocks.0.scale_shift_table:
  shape torch.Size([9, 4096]) from checkpoint, current model is torch.Size([6, 4096])
```

**These files carry the full 61-key transformer config as a GGUF KV field named `config`.** ComfyUI-GGUF surfaces every scalar KV as metadata, ComfyUI merges it, and the model builds with the right dimensions. No custom node, no config pasting — the stock **Unet Loader (GGUF)** just works.

---

## Files

| Quant | Size | Notes |
|---|---|---|
| Q8_0 | ~22 GB | Near-lossless reference |
| Q6_K | ~18 GB | Excellent |
| Q5_K_M | ~15 GB | Very good |
| Q4_K_M | ~13 GB | **Recommended** |
| Q4_K_S | ~13 GB | Slightly smaller |
| Q3_K_M | ~11 GB | Usable, softer detail |
| Q2_K | ~9 GB | Smallest; quality drops sharply |

Grab one file rather than the repo:

```
hf download realrebelai/LTX-2.5_GGUFs LTX-2.5-Distilled-Q4_K_M.gguf --local-dir ComfyUI/models/unet
```

---

## Companion files

The GGUF replaces only the transformer. You also need:

| File | Folder |
|---|---|
| `gemma4-12b-with-proj-ltx-2.5` text encoder | `models/text_encoders` |
| LTX-2.5 **video** VAE | `models/vae` |
| LTX-2.5 **audio** VAE | `models/vae` |

Two VAEs. Missing the audio one is the most common reason a render comes out silent.

The text encoder is **not** stock Gemma — it carries LTX's own projections (`text_embedding_projection`, `audio_projector`) that map prompt embeddings into the DiT's conditioning. A plain Gemma checkpoint will not substitute.

---

## Settings

**Distilled** — few-step schedule, **CFG 1.0**. Guidance is baked into the weights; applying it again degrades output regardless of quantization.

**Dev** — full step count with real CFG.

Use ComfyUI's built-in LTX-2.5 template and swap its model loader for **Unet Loader (GGUF)**. Everything else stays as the template ships it.

---

## Conversion notes

Converted from the official bf16 transformer with a streaming converter, quantized with llama-quantize, then repaired.

Kept at high precision rather than quantized:

```
patchify_proj, audio_patchify_proj, to_gate_logits, scale_shift_table,
keyframes_abs_pos_embedding, caption_projection, time_embed, proj_out, rope
```

**`to_gate_logits` matters more than its size suggests.** Every attention module has one, and they gate how much signal crosses between the audio and video streams. Quantize them and video still looks fine while audio desyncs or degrades — a failure that's easy to ship and hard to diagnose.

llama-quantize does not preserve these layers on its own; they are restored afterward and verified per file. `keyframes_abs_pos_embedding` also has its original `[1, 4096]` shape recorded, since ggml trims trailing singleton dimensions on rewrite.

---

## Credits

- [Lightricks](https://huggingface.co/Lightricks) — LTX-2.5
- [city96](https://github.com/city96/ComfyUI-GGUF) — ComfyUI-GGUF
- [ComfyUI](https://github.com/comfyanonymous/ComfyUI)

Quantized by [RealRebelAI](https://huggingface.co/realrebelai) · [GitHub](https://github.com/RealRebelAI) · [X](https://x.com/realrebelai)