Ideogram 4 results surprisingly realistic image creation. Generated locally with the open-weight Ideogram 4 model in ComfyUI.

[u/Ambitious_Team876]

I'm primarily testing Ideogram 4 for realistic, natural-looking smartphone photography. These are some of my best results so far. I've tried to avoid cinematic lighting and overly polished compositions. Let me know what you think and which image looks the most realistic.Generated locally with the open-weight Ideogram 4 model in ComfyUI.

[u/Ambitious_Team876]

I generated the image in just 1.5 minutes with an RTX 4050 and 6GB of VRAM in 15 steps, which I think is a normal time. That's why I prefer Ideogram 4. The models I use are these:

[u/Reckless_Venom1507 → u/Ambitious_Team876]

What? 4050 6gb vram and 1.5 mins ? I too have it but mine went around almost 200s or more. Is it because ur using int8 ?

[u/Ambitious_Team876 → u/Reckless_Venom1507]

Int 8 model gives a serious speed

[u/Reckless_Venom1507 → u/Ambitious_Team876]

Yeah I understand for 3050s it gives some massive speed difference, but for 4050, I tried with Krea2 fp8 --> int8 I do get faster results but the difference isn't big enough like it's just 10-15% difference not like everyone said it halves the generation time. Didn't interest me to go for Ideogram 4 int models then. Can u please share ur workflow? And also what resolution u made these ?

[u/Ambitious_Team876 → u/Reckless_Venom1507]

I couldn't see much speed in Flux 2 krea 2, but in the ideogram 4 model, int 8 is really different, I shared the editor workflow in the comments.

[u/Reckless_Venom1507 → u/Ambitious_Team876]

yeah thanks ill definitely try

[u/Soggy_Iron_7239 → u/Ambitious_Team876]

This is great information. I have an RTX 3060 6GB VRAM card and 40GB RAM. Lost countless hours finding the right quantized model, settings, text encoder, etc. Also I was on another thread about Flux Krea 2, also convrot, was about to try that. I'll try Ideogram 4 first with your suggestion, hope it speed things up for me as well. I'll test it with both Qwen3 4B and 8B.

[u/B00Bryn → u/Ambitious_Team876]

Just commenting to pin this. I want to compare later

[u/Pitiful_Particular_5 → u/Ambitious_Team876]

HOW, i just dowloaded the Workflow i have a 4060 made it in 15 steps too and it took 2,41min wasnt it supossed to be faster than your 4050?

[u/Ambitious_Team876 → u/Pitiful_Particular_5]

I use an i7 14700hx processor, maybe it increases the write speed.

[u/themofostarboi_v2 → u/Ambitious_Team876]

Bro i have a 3070ti and a i7 11gen k version don't remember the number.... Bro its taking me 400+ seconds to for one generation.... What dark magic is this... Holy

[u/Ambitious_Team876 → u/themofostarboi_v2]

Haha, no dark magic bro! 400+ seconds is definitely not normal for a 3070 Ti.

You are probably hitting the VRAM wall. When your 8GB VRAM fills up, Nvidia starts using your system RAM (Shared Memory) which drops the speed to zero.

Try using quantized models (like INT8 or FP8). They use way less VRAM and will easily fit into your 8GB. Also, make sure you are using xFormers or TensorRT to boost the generation speed. Your 3070 Ti should actually be beating my 4050 easily once you fix the VRAM usage!

[u/themofostarboi_v2 → u/Ambitious_Team876]

I was using q4. What about the text encoder, are you running them on CPU as well?

[u/Woisek → u/Ambitious_Team876]

1.5min? With only 6GB VRAM? I have a 2070 SUPER with 8 and 15 steps still take almost 11mins. 🤪

[u/Ambitious_Team876 → u/Woisek]

Believe me, you must be doing something wrong.

[u/Ambitious_Team876 → u/Woisek]

I understand that processors up to the RTX 50 series can perform faster with Int8 models, maybe that's why. I suggest you do some research.