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ideogram-4-non-commercial
Model source
Source description
Quantized GGUF diffusion transformer weights for Ideogram 4, converted from the original FP8 release for use with ComfyUI GGUF loader nodes.
This repository contains GGUF files for the two Ideogram 4 diffusion components:
Sources
1 sourceVerified Sep 30
Model artifacts
10 artifactsSource excerpts
2 excerpts
ideogram4-transformer-*.gguf: the main text-guided diffusion transformer.ideogram4-unconditional_transformer-*.gguf: the unconditional transformer used by CFG workflows.These files are not a complete standalone Ideogram 4 package. Your workflow still needs the other runtime assets expected by Ideogram 4 in ComfyUI, such as the text or multimodal encoder components and VAE.
Use these models with the ComfyUI nodes from molbal/ComfyUI-GGUF. Install that custom node repository into your ComfyUI custom_nodes folder, then restart ComfyUI.
Place the downloaded .gguf files in one of ComfyUI's diffusion model folders:
ComfyUI/models/diffusion_models/
ComfyUI/models/unet/
Load the files with Unet Loader (GGUF) or Unet Loader (GGUF/Advanced) in an Ideogram 4 workflow that accepts separate main and unconditional diffusion models.
Each quant level is published for both the main transformer and the unconditional transformer.
| Quant | Main transformer | Unconditional transformer | Approx. size per file |
|---|---|---|---|
| Q4_0 | ideogram4-transformer-q4_0.gguf | ideogram4-unconditional_transformer-q4_0.gguf | 5.64 GB |
| Q4_1 | ideogram4-transformer-q4_1.gguf | ideogram4-unconditional_transformer-q4_1.gguf | 6.21 GB |
| Q5_0 | ideogram4-transformer-q5_0.gguf | ideogram4-unconditional_transformer-q5_0.gguf | 6.77 GB |
| Q5_1 | ideogram4-transformer-q5_1.gguf | ideogram4-unconditional_transformer-q5_1.gguf | 7.33 GB |
| Q8_0 | ideogram4-transformer-q8_0.gguf | ideogram4-unconditional_transformer-q8_0.gguf | 10.14 GB |
The main and unconditional models do not need to use the same quant level.
| Main transformer | Unconditional transformer | Notes |
|---|---|---|
q8_0 | q8_0 | Highest precision GGUF pair in this repo. |
q8_0 | q5_1 | Keeps the main transformer high precision while reducing memory on the unconditional side. |
q8_0 | q4_1 | Larger quality bias toward the main transformer with lower CFG-side memory. |
q5_1 | q4_1 | Balanced quality and size. |
q5_0 | q4_1 | Lower memory starting point. |
q4_0 | q4_0 | Smallest available GGUF pair. |
The chart below shows peak RAM and VRAM measured during Ideogram 4 inference with different main/unconditional quant pairings, including an NVFP4 baseline for comparison.
Peak memory usage of GGUF quants and NVFP4
The chart below compares relative per-iteration inference speed across quant pairings, with the NVFP4 + NVFP4 run used as the 100% reference in the chart.
Ideogram 4 inference speed among various quantization combinations
Measurements were taken by u/molbal on Windows 11 with an AMD Ryzen 7 6800H CPU, 48 GB RAM, and an RTX 3080 Laptop GPU with 8 GB VRAM. Exact memory use and speed will vary by workflow, image size, sampler settings, ComfyUI version, and loaded auxiliary models.
Download the two files you want to pair from the Files tab, or use the Hugging Face CLI. For example:
huggingface-cli download molbal/ideogram-4-gguf ideogram4-transformer-q5_1.gguf ideogram4-unconditional_transformer-q4_1.gguf --local-dir ComfyUI/models/diffusion_models
These are non-K GGUF quantizations intended for PyTorch dequantization in ComfyUI. K-quants are not included because this ComfyUI loading path does not use fused quantized linear kernels.
If a workflow fails to load these files, update molbal/ComfyUI-GGUF and confirm that both the main and unconditional transformer files are present in a ComfyUI diffusion model folder.
These files are derived from ideogram-ai/ideogram-4-fp8 and follow the Ideogram 4 non-commercial license.
ideogram4-transformer-q5_0.gguf
gguf · 6.30 GB · SHA-256 eccaf81a4637…2803 · Hugging Face
ideogram4-unconditional_transformer-q4_0.gguf
gguf · 5.26 GB · SHA-256 03abe8277cf9…fc7c · Hugging Face
Downloadideogram4-unconditional_transformer-q4_1.gguf
gguf · 5.78 GB · SHA-256 ae7d15614539…c040 · Hugging Face
Downloadideogram4-unconditional_transformer-q5_0.gguf
gguf · 6.30 GB · SHA-256 7c5648270f00…1a05 · Hugging Face
Downloadideogram4-unconditional_transformer-q5_1.gguf
gguf · 6.83 GB · SHA-256 cb7ad55732cf…18ca · Hugging Face
Downloadideogram4-unconditional_transformer-q8_0.gguf
gguf · 9.44 GB · SHA-256 39ab8b413406…5a1a · Hugging Face
Download--- license: other license_name: ideogram-4-non-commercial license_link: https://huggingface.co/ideogram-ai/ideogram-4-fp8/blob/main/LICENSE.md base_model: - ideogram-ai/ideogram-4-fp8 pipeline_tag: text-to-image tags: - text-to-image - image-generation - diffusion - flow-matching - dit - ideogram - quantization - gguf - comfyui --- # Ideogram 4 GGUF Quantized GGUF diffusion transformer weights for [Ideogram 4](https://huggingface.co/ideogram-ai/ideogram-4-fp8), converted from the original FP8 release for use with ComfyUI GGUF loader nodes. This repository contains GGUF files for the two Ideogram 4 diffusion components: - `ideogram4-transformer-*.gguf`: the main text-guided diffusion transformer. - `ideogram4-unconditional_transformer-*.gguf`: the unconditional transformer used by CFG workflows. These files are not a complete standalone Ideogram 4 package. Your workflow still needs the other runtime assets expected by Ideogram 4 in ComfyUI, such as the text or multimodal encoder components and VAE. ## ComfyUI Support Use these models with the ComfyUI nodes from [molbal/ComfyUI-GGUF](https://github.com/molbal/ComfyUI-GGUF). Install that custom node repository into your ComfyUI `custom_nodes` folder, then restart ComfyUI. Place the downloaded `.gguf` files in one of ComfyUI's diffusion model folders: ```text ComfyUI/models/diffusion_models/ ComfyUI/models/unet/ ``` Load the files with `Unet Loader (GGUF)` or `Unet Loader (GGUF/Advanced)` in an Ideogram 4 workflow that accepts separate main and unconditional diffusion models. ## Files Each quant level is published for both the main transformer and the unconditional transformer. | Quant | Main transformer | Unconditional transformer | Approx. size per file | | --- | --- | --- | --- | | Q4_0 | `ideogram4-transformer-q4_0.gguf` | `ideogram4-unconditional_transformer-q4_0.gguf` | 5.64 GB | | Q4_1 | `ideogram4-transformer-q4_1.gguf` | `ideogram4-unconditional_transformer-q4_1.gguf` | 6.21 GB | | Q5_0 | `ideogram4-transformer-q5_0.gguf` | `ideogram4-unconditional_transformer-q5_0.gguf` | 6.77 GB | | Q5_1 | `ideogram4-transformer-q5_1.gguf` | `ideogram4-unconditional_transformer-q5_1.gguf` | 7.33 GB | | Q8_0 | `ideogram4-transformer-q8_0.gguf` | `ideogram4-unconditional_transformer-q8_0.gguf` | 10.14 GB | The main and unconditional models do not need to use the same quant level. ## Suggested...
Source context: 94053 downloads · 10 likes · Pipeline text-to-image · Repo molbal/ideogram-4-gguf