Can the RTX 3090 24 GB run Ideogram 4?
Yes, but only just: Q8_0 leaves 1.4 GB free on the RTX 3090 24 GB.
Q8_0 (10.1 GB (×2, both loaded)) fits with only 1.4 GB to spare (about 22.6 GB of 24 GB).
01What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | ideogram4-transformer-q8_0.gguf main model Q8_0 · molbal/ideogram-4-gguf | models/unet | 10.1 GB | Download → |
| Model | ideogram4-unconditional_transformer-q8_0.gguf unconditional model, loaded together with the main one Q8_0 · molbal/ideogram-4-gguf | models/unet | 10.1 GB | Download → |
| Text encoder | qwen3vl_8b_fp8_scaled.safetensors Qwen3-VL 8B FP8 · Comfy-Org/Ideogram-4 | models/text_encoders | 10.6 GB | Download → |
| VAE | flux2-vae.safetensors FLUX.2 VAE · Comfy-Org/Ideogram-4 | models/vae | 0.3 GB | Download → |
| Total download · keep about the same free on disk | 31.2 GB | |||
Alternatives: Qwen3-VL 8B NVFP4 (6.3 GB). FP4 files are listed only as alternatives unless the GPU is an RTX 50 (Blackwell). Sizes from Hugging Face, 2026-10-01.
System RAM: 48 GB or more. These files (both noise models) take about 31.2 GB of RAM while loaded, 37.2 GB with Windows and ComfyUI. What happens with less. calculated
02Every Ideogram 4 file on 24 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| Q8_0 ← GGUF · molbal | 10.1 GB ×2 | 22.6 GB | fits · 1.4 GB spare | practically identical to the original | Hugging Face → |
| FP8 SAFETENSORS · Comfy-Org | 9.3 GB ×2 | 20.9 GB | fits · 3.1 GB spare | practically identical to the original | Hugging Face → |
| INT8 SAFETENSORS · Comfy-Org | 9.6 GB ×2 | 21.5 GB | fits · 2.5 GB spare | practically identical to the original | Hugging Face → |
| Q5_1 GGUF · molbal | 7.3 GB ×2 | 17.0 GB | fits · 7.0 GB spare | close; small differences in fine detail | Hugging Face → |
| Q4_1 GGUF · molbal | 6.2 GB ×2 | 14.7 GB | fits · 9.3 GB spare | good; some loss in fine detail and text | Hugging Face → |
“Needed” adds 1.5 GB of working memory for Ideogram 4 and a 0.8 GB reserve. Sizes 2026-10-01. Needs two transformer files loaded together (main + unconditional). GGUF files need the molbal fork of ComfyUI-GGUF. No 16-bit weights were released.
03Measured and reported results
Nobody has sent measured numbers for this pair yet. If you run Ideogram 4 on a RTX 3090 24 GB, send your time per image and peak VRAM and it will appear here, credited.
04About the RTX 3090 24 GB
The RTX 3090 24 GB (Ampere) has no FP8 compute. FP8 files still load and save memory, but ComfyUI converts them back before the maths, so there is no speed gain - Q8_0 GGUF is the closer-to-original 8-bit choice. ComfyUI can compute INT8 files natively on NVIDIA, which is worth a try where a model offers one.
24 GB GDDR6X · 384-bit · 936 GB/s · Ampere. Everything that runs on it →
05Questions
How much VRAM does Ideogram 4 need?
Around 14.7 GB with the smallest file (Q4_1) and 20.9 GB with an 8-bit file (FP8).
Which Ideogram 4 file should I download for the RTX 3090 24 GB?
Q8_0 (10.1 GB) from molbal/ideogram-4-gguf. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.
FP8 or Q8_0 for Ideogram 4 on the RTX 3090 24 GB?
Q8_0 (10.1 GB). The RTX 3090 24 GB has no FP8 maths, so FP8 (9.3 GB) only saves memory and is a step further from the original.
How much do I need to download for Ideogram 4 on the RTX 3090 24 GB?
31.2 GB: ideogram4-transformer-q8_0.gguf, ideogram4-unconditional_transformer-q8_0.gguf, qwen3vl_8b_fp8_scaled.safetensors, flux2-vae.safetensors.