Can the RTX 4090 24 GB run Ideogram 4?
Download FP8 (9.3 GB (×2, both loaded)). With the model's working memory it needs about 20.9 GB, leaving 3.1 GB spare on 24 GB. Quality: practically identical to the original.
01What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | ideogram4_fp8_scaled.safetensors main model FP8 · Comfy-Org/Ideogram-4 | models/diffusion_models | 9.3 GB | Download → |
| Model | ideogram4_unconditional_fp8_scaled.safetensors unconditional model, loaded together with the main one FP8 · Comfy-Org/Ideogram-4 | models/diffusion_models | 9.3 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 | 29.5 GB | |||
Alternatives: Qwen3-VL 8B NVFP4 (6.3 GB). The 16-bit text encoder is a little more faithful; the smaller one is chosen here because it loads faster and needs less RAM. FP4 files are listed only as alternatives unless the GPU is an RTX 50 (Blackwell). Sizes read from Hugging Face (2026-09-25). “Download” links start the file directly; the file name links are the same files the official ComfyUI workflows use.
System RAM: 48 GB or more. ComfyUI keeps the model files, the text encoder and the VAE in system RAM and moves them to the GPU as needed. With this set of files that is about 29.5 GB, plus roughly 6 GB for Windows, ComfyUI and a browser: 35.5 GB in total. With less RAM it still runs, but Windows starts swapping to disk and loading gets very slow. calculated
02Every Ideogram 4 file on 24 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| FP8 ← SAFETENSORS · Comfy-Org | 9.3 GB ×2 | 20.9 GB | fits · 3.1 GB spare | practically identical to the original | Hugging Face → |
| Q8_0 GGUF · molbal | 10.1 GB ×2 | 22.6 GB | fits · 1.4 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 → |
Sizes from the Hugging Face file listing, read 2026-09-25. “Needed” = file ×2 + 1.5 GB working memory for this model + 0.8 GB kept free for the system. Needs two transformer files loaded together (main + unconditional). GGUF files need the molbal fork of ComfyUI-GGUF. No 16-bit weights were released.
03The text encoder
Qwen3-VL 8B: 10.6 GB as FP8, 6.3 GB as NVFP4. ComfyUI encodes the prompt first and can push the encoder out of VRAM before sampling, so it does not have to fit together with the model. On 24 GB the FP8 encoder fits on its own, so prompt encoding stays fast.
04About this GPU
The RTX 4090 24 GB is an Ada Lovelace GPU with hardware FP8, so ComfyUI can compute Comfy-Org's FP8 files natively: small and fast. (Plain FP8 files use FP8 maths with the --fast fp8_matrix_mult option.)
RTX 4090 24 GB: 24 GB GDDR6X · 384-bit · 1008 GB/s · Ada Lovelace. Everything that runs on the RTX 4090 24 GB →
05What more VRAM would change
Nothing to gain for this model: the RTX 4090 24 GB already runs a top-quality file entirely in VRAM. More memory would only help with bigger images, longer clips or several models at once.
What changes from the RTX 4090 24 GB to the RTX 5090 32 GB →
06Measured and reported results
Nobody has sent measured numbers for this pair yet. If you run Ideogram 4 on a RTX 4090 24 GB, send your time per image and peak VRAM and it will appear here, credited.
07Questions
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), counting working memory and a small system reserve.
Which Ideogram 4 file should I download for the RTX 4090 24 GB?
FP8 (9.3 GB) from Comfy-Org/Ideogram-4.
Is FP8 faster than GGUF on the RTX 4090 24 GB?
It can be. This GPU has FP8 hardware, and ComfyUI computes FP8 natively for files made for it (Comfy-Org's fp8_scaled files), or for any FP8 file with the --fast fp8_matrix_mult option. GGUF files are unpacked on the fly, which costs some speed.
How much do I need to download for Ideogram 4 on the RTX 4090 24 GB?
About 29.5 GB for the model file, text encoder and VAE listed on this page, and the same again free on disk. With a 24 GB card, 48 GB of system RAM or more is recommended.