ComfyUI GPT Image Direct

ComfyUI-GPT-Image-Direct

OpenAI GPT Image 2.5 (Flare and Sunburst), GPT Image 2, 1.5 and 1-mini in ComfyUI, on your own API key.

No Comfy credits, no middleman, no markup. One node, text-to-image and reference editing, exact USD cost printed after every run.

Why

ComfyUI's built-in OpenAI partner node bills through Comfy.org credits. Its own price badge quotes about 1.4x OpenAI's list price, and the credit table on docs.comfy.org implies more than that once you buy credits in packs. This node sends the same request to the same OpenAI endpoint with your key, and reads the real token usage back so you see what each image actually cost.

Node

| Node | What it does | |------|--------------| | GPT Image Generate (Direct API) | Text-to-image, or edit up to 16 reference images with an optional inpaint mask. Outputs the image batch, an alpha mask (for transparent backgrounds), a cost_info string and a cache_key. |

Category: AKURATE/GPT Image Direct

Inputs

• model: gpt-image-2.5-flare (fast, everyday), gpt-image-2.5-sunburst (slower, more precise text and layouts), gpt-image-2, gpt-image-1.5, gpt-image-1-mini. Flare and Sunburst cost the same per token.
• quality: low, medium, high, xhigh, max, auto. This is the cost lever. Rough 1024x1024 prices at list rate: low ~$0.006, medium ~$0.02, high ~$0.05, max ~$0.21. xhigh and max exist on 2.5 only; other models fall back to high.
• size: presets up to 3840x2160 or custom (multiples of 16, aspect 1:3 to 3:1, 480 to 3840 px per edge). Legacy models fall back to 1024x1024 for sizes they lack.
• background: auto, opaque, transparent (forces png or webp; the alpha lands on the mask output).
• output_format and output_compression: png, jpeg or webp. File format only, no effect on cost.
• moderation: auto or low.
• n: images per run, 1 to 8.
• seed: not sent to OpenAI (the API has no seed). Changing it forces a re-run and a fresh cache_key.
• image_1 to image_4 (optional): individual reference sockets, any sizes. images (optional): a batch appended after them. 16 references total. Any reference switches to the edits endpoint.
• mask (optional): white = repaint. Needs exactly one reference image. Auto-resized to the reference.
• reference_max_size: downscale references before upload (2048 default). Smaller references mean fewer input tokens.
• input_fidelity: auto (not sent), low, high. Edits only. High keeps more of the reference but costs more input tokens.
• api_key, api_base, timeout_sec: override the key, point at an OpenAI-compatible base URL (Azure, fal, a proxy), and give slow max-quality 4K runs more time.

Outputs

• images: IMAGE batch.
• mask: MASK, 1 where the image is transparent (same convention as Load Image).
• cost_info: "$0.0528 USD (exact) | gpt-image-2.5-flare high 1536x1024 x1 | 14.2s | tokens: 24 text-in, 0 img-in, 0 cached, 1756 out | gpt_image_20260919_120000_00.png". Exact when the API returns usage, otherwise labelled (estimated).
• cache_key: deterministic string of every input, for Hash Vault in ComfyUI-API-Optimizer.

Images are also saved to output/gpt_image_direct/.

Installation

1. Copy this folder into ComfyUI/custom_nodes/ (or clone it there).
2. No extra pip installs. It uses requests and Pillow, which ComfyUI already ships.
3. Restart ComfyUI.

API key

Resolution order:

1. The api_key input on the node
2. OPENAI_API_KEY environment variable
3. openai_api_key.txt in your ComfyUI root (next to main.py)

Get a key at https://platform.openai.com/api-keys. GPT Image models need a one-time Organization Verification at https://platform.openai.com/settings/organization/general. Without it the node reports the 401/403 with a pointer to that page.

Keeping it cheap

• quality=low for iteration, medium for most finals. high is 9x low, max is 35x low.
• Keep references at 1024 unless the edit needs detail. Every reference image costs input tokens on every call.
• Leave input_fidelity on auto unless the reference must survive pixel-exact.
• Wide and tall presets (1536x1024, 1024x1536) often cost slightly less than square at the same quality.
• For big offline batches, OpenAI's Batch API is half price. That is a separate async workflow, not this node.

Pricing reference

USD per 1M tokens, OpenAI list price as of 2026-09-19:

| Model | Text in | Cached in | Image in | Image out | |-------|---------|-----------|----------|-----------| | gpt-image-2.5-flare / sunburst | 5.00 | 1.25 | 8.00 | 30.00 | | gpt-image-2 | 5.00 | 1.25 | 8.00 | 30.00 | | gpt-image-1.5 | 5.00 | 1.25 | 8.00 | 32.00 | | gpt-image-1-mini | 2.00 | 0.20 | 2.50 | 8.00 |

The node multiplies the usage counts the API returns by this table. Update PRICE_PER_1M in gpt_image_direct_nodes.py if OpenAI changes prices.

Testing

python tools/test_gpt_image_direct.py          # offline, mocked HTTP, no spend
python tools/test_gpt_image_direct.py --live   # plus one real low-quality Flare call (~$0.006)

License

MIT