Can the RTX 4050 Laptop 6 GB run Ideogram 4?
Not realistically: the smallest Ideogram 4 file still needs about 15 GB.
Even the smallest file (Q4_1, 6.2 GB (×2, both loaded)) needs about 14.7 GB, far beyond 6 GB. It may start with heavy offloading, but this is not a realistic everyday setup. Pick a smaller model or a GPU with more memory.
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.
02Every Ideogram 4 file on 6 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| FP8 SAFETENSORS · Comfy-Org | 9.3 GB ×2 | 20.9 GB | 14.9 GB too big | practically identical to the original | Hugging Face → |
| INT8 SAFETENSORS · Comfy-Org | 9.6 GB ×2 | 21.5 GB | 15.5 GB too big | practically identical to the original | Hugging Face → |
| Q8_0 GGUF · molbal | 10.1 GB ×2 | 22.6 GB | 16.6 GB too big | practically identical to the original | Hugging Face → |
| Q5_1 GGUF · molbal | 7.3 GB ×2 | 17.0 GB | 11.0 GB too big | close; small differences in fine detail | Hugging Face → |
| Q4_1 ← GGUF · molbal | 6.2 GB ×2 | 14.7 GB | 8.7 GB too big | 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.
03What 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). 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
At 6.3 GB even the smallest Qwen3-VL 8B file is too big for 6 GB, so it runs from system RAM. That slows down reading the prompt, not the picture. 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 4050 Laptop 6 GB, send your time per image and peak VRAM and it will appear here, credited.
06About the RTX 4050 Laptop 6 GB
The RTX 4050 Laptop 6 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.
6 GB GDDR6 · 96-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 4050 Laptop 6 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 4050 Laptop 6 GB?
FP8 (9.3 GB): the RTX 4050 Laptop 6 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 4050 Laptop 6 GB?
23.3 GB: ideogram4-transformer-q4_1.gguf, ideogram4-unconditional_transformer-q4_1.gguf, qwen3vl_8b_fp8_scaled.safetensors, flux2-vae.safetensors.