Check my GPU →

Can the RTX 4070 Laptop 8 GB run Ideogram 4?

Not entirely. Even Q4_1 is 6.7 GB over 8 GB, so ComfyUI keeps part of it in system RAM.

Image model · 9.3B8 GB GDDR6 · 128-bit · Ada Lovelace · 35–115 WData 2026-10-01
Offload
Not entirely in VRAM, but it can still run.

The smallest sensible file, Q4_1 (6.2 GB (×2, both loaded)), needs about 14.7 GB - 6.7 GB more than RTX 4070 Laptop 8 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.

Best fileQ4_1
File size6.2 GB ×2
VRAM needed~14.7 GB
System RAM32 GB+
Memory map · RTX 4070 Laptop 8 GB14.7 GB needed · 6.7 GB over 8 GB
07 GB15 GB
Weights Q4_1 ×2 · 12.4 GBWorking memory · 1.5 GBReserve · 0.8 GBSpills to system RAM · 6.7 GB

Also try the FP8 file (9.3 GB) on this GPU. It does not fit entirely, but a current ComfyUI streams the overflow from RAM and native 8-bit files often beat a small GGUF that does fit. Dynamic VRAM →

01With more VRAM

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 Laptop 8 GB to the RTX 3090 24 GB →

02Every Ideogram 4 file on 8 GB

FileSizeNeededOn this cardQualityDownload
FP8
SAFETENSORS · Comfy-Org
9.3 GB ×220.9 GB12.9 GB too bigpractically identical to the originalHugging Face →
INT8
SAFETENSORS · Comfy-Org
9.6 GB ×221.5 GB13.5 GB too bigpractically identical to the originalHugging Face →
Q8_0
GGUF · molbal
10.1 GB ×222.6 GB14.6 GB too bigpractically identical to the originalHugging Face →
Q5_1
GGUF · molbal
7.3 GB ×217.0 GB9.0 GB too bigclose; small differences in fine detailHugging Face →
Q4_1 ←
GGUF · molbal
6.2 GB ×214.7 GB6.7 GB too biggood; some loss in fine detail and textHugging 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.

03What to download

PartFileFolderSize
Modelideogram4-transformer-q4_1.gguf
main model
Q4_1 · molbal/ideogram-4-gguf
models/unet6.2 GBDownload →
Modelideogram4-unconditional_transformer-q4_1.gguf
unconditional model, loaded together with the main one
Q4_1 · molbal/ideogram-4-gguf
models/unet6.2 GBDownload →
Text encoderqwen3vl_8b_fp8_scaled.safetensors
Qwen3-VL 8B FP8 · Comfy-Org/Ideogram-4
models/text_encoders10.6 GBDownload →
VAEflux2-vae.safetensors
FLUX.2 VAE · Comfy-Org/Ideogram-4
models/vae0.3 GBDownload →
Total download · keep about the same free on disk23.3 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.

04The text encoder

Take the smallest Qwen3-VL 8B file (6.3 GB): it is the only one that fits in 8 GB on its own. Sizes: FP8 10.6 GB, NVFP4 6.3 GB. Why the encoder does not count against VRAM →

05Measured and reported results

Nobody has sent measured numbers for this pair yet. If you run Ideogram 4 on a RTX 4070 Laptop 8 GB, send your time per image and peak VRAM and it will appear here, credited.

06About the RTX 4070 Laptop 8 GB

The RTX 4070 Laptop 8 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.) As a laptop GPU it runs at a lower power limit than desktop cards (35–115 W depending on the laptop). The memory verdicts are the same; speed depends heavily on how much power the laptop maker allows.

8 GB GDDR6 · 128-bit · Ada Lovelace · 35–115 W. Everything that runs on it →

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).

Which Ideogram 4 file should I download for the RTX 4070 Laptop 8 GB?

Q4_1 (6.2 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 4070 Laptop 8 GB?

FP8 (9.3 GB): the RTX 4070 Laptop 8 GB computes it natively, while Q8_0 (10.1 GB) is unpacked on the fly.

How much do I need to download for Ideogram 4 on the RTX 4070 Laptop 8 GB?

23.3 GB: ideogram4-transformer-q4_1.gguf, ideogram4-unconditional_transformer-q4_1.gguf, qwen3vl_8b_fp8_scaled.safetensors, flux2-vae.safetensors.