Can the RTX 4070 12 GB run Ideogram 4?
The smallest sensible file, Q4_1 (6.2 GB (×2, both loaded)), needs about 14.7 GB — 2.7 GB more than RTX 4070 12 GB has. ComfyUI can still run it by streaming part of the model from system RAM. How much slower that is depends on your ComfyUI version, the file format and the PCIe link — see the note below.
Worth trying on this GPU: with an up-to-date ComfyUI, Dynamic VRAM (on by default for NVIDIA since March 2026) streams whatever does not fit from system RAM, and ComfyUI's own start-up message recommends native FP8/INT8 files over GGUF, saying they “will be faster even if they are larger than your memory”. So before settling for a heavily compressed GGUF, try the native FP8 file (9.3 GB). The file recommended above is the best one that fits entirely — the safe choice on older ComfyUI versions, AMD and Intel. Comfy blog: Dynamic VRAM →
01What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | ideogram4-transformer-q4_1.gguf main model Q4_1 · molbal/ideogram-4-gguf | models/unet | 6.2 GB | Download → |
| Model | ideogram4-unconditional_transformer-q4_1.gguf unconditional model, loaded together with the main one Q4_1 · molbal/ideogram-4-gguf | models/unet | 6.2 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 | 23.3 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: 32 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 23.3 GB, plus roughly 6 GB for Windows, ComfyUI and a browser: 29.3 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 12 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| FP8 SAFETENSORS · Comfy-Org | 9.3 GB ×2 | 20.9 GB | 8.9 GB too big | practically identical to the original | Hugging Face → |
| Q8_0 GGUF · molbal | 10.1 GB ×2 | 22.6 GB | 10.6 GB too big | practically identical to the original | Hugging Face → |
| INT8 SAFETENSORS · Comfy-Org | 9.6 GB ×2 | 21.5 GB | 9.5 GB too big | practically identical to the original | Hugging Face → |
| Q5_1 GGUF · molbal | 7.3 GB ×2 | 17.0 GB | 5.0 GB too big | close; small differences in fine detail | Hugging Face → |
| Q4_1 ← GGUF · molbal | 6.2 GB ×2 | 14.7 GB | 2.7 GB too big | 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 12 GB the FP8 encoder fits on its own, so prompt encoding stays fast.
04About this GPU
The RTX 4070 12 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 4070 12 GB: 12 GB GDDR6X · 192-bit · 504 GB/s · Ada Lovelace. Everything that runs on the RTX 4070 12 GB →
05What more VRAM would change
With 24 GB you could run Ideogram 4 at 8-bit or better (FP8, 9.3 GB) with no offloading: for example on the RTX 4090 24 GB, RTX 3090 24 GB, RX 7900 XTX 24 GB.
What changes from the RTX 4070 12 GB to the RTX 4070 Ti Super 16 GB → · What changes from the RTX 4070 12 GB to the RTX 3090 24 GB →
06Measured and reported results
Nobody has sent measured numbers for this pair yet. If you run Ideogram 4 on a RTX 4070 12 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 4070 12 GB?
Q4_1 (6.2 GB) from molbal/ideogram-4-gguf. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.
Is FP8 faster than GGUF on the RTX 4070 12 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 4070 12 GB?
About 23.3 GB for the model file, text encoder and VAE listed on this page, and the same again free on disk. With a 12 GB card, 32 GB of system RAM or more is recommended.