Image generation costs can vary depending on image size, quality, and the request itself.
OpenAI prices GPT Images 2 by tokens, so the cost varies by output size and quality. Their examples show a 1024x1024 image at around $0.006 for low quality, $0.053 for medium, and $0.211 for high.
Nano Banana Pro / Gemini 3 Pro Image Preview is priced more like a per-image cost, with Google listing it around $0.134 for 1K/2K images and $0.24 for 4K images.
Thanks so much for this breakdown, @danny_support â super helpful and very thorough.
I really appreciate you walking through the different pricing models and giving concrete ballpark numbers for each option. Thatâs exactly what I was wondering about too, so Iâm also grateful to @motheraigaia for asking the question in the first place.
Thanks for documenting your findings, your questions dig deep into not only how Pickaxe interacts with the GPT Image 2.0 action but also how OpenAI have designed their model to work.
Iâll try to answer them to the best of my understanding.
If GPT Image 2 generates the image, does the selected agent model still matter?
Yes. GPT Image 2 is the model actually rendering the image. But in a workflow tool like Pickaxe, the LLM you select like Gemini, GPT, or Claude is usually the model reading the transcript, deciding what to do, preparing the prompt, and calling the image action.
How do I get ChatGPT-quality infographics in Pickaxe
I noticed you selected the model used in Pickaxe as GPT-5. The beautiful infographics you were able to create in ChatGPT are actually using the most recent model released, GPT-5.5. This makes a pretty big difference and through my testing should net you the largest improvement in infographic quality.
Where does the âthinkingâ happen? Is it the the agent or the image model?
The reasoning slider controls how long and thorough the chat LLMâs reasoning is before answering and calling the image tool. Only the final prompt string the LLM emits ever reaches the image model (doesnât pass the transcript). Internally OpenAI could be providing that to the image model but weâre not entirely sure.
Lastly, if you are worried about image generation timing out - you can try lowering the reasoning level and cutting the prompt down that the Wingman created since over-long prompts can be detrimental.
Let me know if you have any questions or interesting findings but it is very cool to learn about how these things work behind the scenes.
Wow, this was really helpful. Thank you so much for getting back to me.
It makes perfect sense that GPTâ5.5 is what Iâve been using to get these results I really like.
I did end up creating a duplicate, and that was really helpful to simplify the prompt.
I see your photo was great looking. Thatâs along the lines of what I was hoping for. Can I ask you what level of reasoning you used for your 5.5 infographic you made to get those results?
Your Response was so helpful, and I appreciate your graphic example too.