How do I generate images with a transparent background (PNG cutouts)?

Short answer

Use gpt-image-2 and add two fields to the request:

{
  "model": "gpt-image-2",
  "prompt": "a cute cartoon fox sticker, clean cutout edges, no shadow",
  "background": "transparent",
  "output_format": "png"
}

The image comes back as a PNG with a real alpha channel — no cutout post-processing required. Text-to-image, image editing, and the Responses image tool all support it.

background: "transparent" is a capability OpenAI opened up for GPT-Image-2 on 2026-08-21 (marked preview by OpenAI). APIYI has verified it end to end: both text-to-image and image editing return true alpha transparency.

Which models can produce transparent backgrounds

Model	How	Reliability
`gpt-image-2`	Parameter — `background: "transparent"` with `output_format` set to `png` or `webp`	✅ Reliable, recommended
`gpt-image-1.5` / `gpt-image-1`	Same parameter	✅ Reliable (older models; new projects should just use `gpt-image-2`)
`gpt-image-2-all` / `gpt-image-2-vip`	No `background` parameter — you can only ask for it in the prompt	⚠️ Occasionally unreliable; the same prompt may still come back on white
`seedream-5-0` / `seedream-5-0-pro`	`output_format: "png"` plus `transparent background, alpha channel` in the prompt	⚠️ Prompt-driven, alpha is not guaranteed on every call
Gemini image models (Nano Banana family)	Prompt only	⚠️ Same as above
`seedream-4-5` / `seedream-4-0`	`jpeg` output only, no alpha channel	❌ Not supported

If you need transparency reliably, use gpt-image-2. A parameter and a prompt request are not the same thing: the first is guaranteed by the API, the second is the model doing its best. At batch scale the difference shows.

Three ways to call it

Text-to-image `/v1/images/generations`

curl https://api.apiyi.com/v1/images/generations \
  -H "Authorization: Bearer $APIYI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-image-2",
    "prompt": "a cute cartoon fox sticker, flat vector illustration, single centered subject, clean cutout edges, no background, no shadow",
    "background": "transparent",
    "output_format": "png",
    "quality": "low"
  }'

Image editing `/v1/images/edits`

Hand it an ordinary photo and ask it to drop the background:

curl https://api.apiyi.com/v1/images/edits \
  -H "Authorization: Bearer $APIYI_API_KEY" \
  -F model=gpt-image-2 \
  -F [email protected] \
  -F 'prompt=remove the background completely and keep only the fox, clean cutout edges, no shadow' \
  -F background=transparent \
  -F output_format=png

Mask-based inpainting (mask) and a transparent background work together — they do not conflict.

Responses image tool

{
  "model": "gpt-5.2",
  "input": "Generate a cartoon fox sticker",
  "tools": [{
    "type": "image_generation",
    "model": "gpt-image-2",
    "background": "transparent",
    "output_format": "png"
  }]
}

The returned image_generation_call echoes "background": "transparent".

Why `jpeg` does not work

JPEG has no alpha channel — there is nowhere to store transparency. Combining output_format: "jpeg" with background: "transparent" returns a 400:

{
  "error": {
    "message": "Transparent background is not supported for JPEG output format",
    "param": "background",
    "code": "invalid_value"
  }
}

For transparency pick png (lossless, larger) or webp (lossy and tunable, smaller, also supports alpha). webp additionally accepts output_compression to trim file size.

Editing is a re-draw, not a precise cutout

Set expectations here up front: when /v1/images/edits runs with background: transparent, the model understands the scene and paints the subject again rather than tracing the original outline the way Photoshop would. That means:

The subject’s pose, style, and fine detail will shift — this is not pixel-level preservation
To stay closer to the original, use quality: "high" and state “keep the original composition, do not change the subject’s appearance” in the prompt
If your workflow needs pixel-exact extraction, do the cutout yourself with rembg, PIL, or sharp. Model generation is a better fit for “produce reusable assets” than for exact matting

Billing

Transparency costs nothing extra. At the same quality tier and size, background: "transparent" and background: "opaque" consume exactly the same number of image tokens, billed under the normal per-token rules for gpt-image-2.

Common errors

400: Transparent background is not supported for JPEG output format

output_format was set to jpeg. Switch it to png or webp.

The image really is on white, not transparent

Check three things. First, that the background field actually reached the API — the edits endpoint is multipart/form-data, so it must be -F background=transparent rather than a JSON body field. Second, whether the top-level background in the response echoes transparent. Third, whether you are on gpt-image-2 — gpt-image-2-all and gpt-image-2-vip have no such parameter and silently ignore it.

How do I confirm the image really has an alpha channel

One Python snippet is enough:

from PIL import Image
im = Image.open("out.png")
print(im.mode)                      # RGBA means it has alpha
a = im.convert("RGBA").getchannel("A")
print(a.histogram()[0] / (im.width * im.height))   # share of fully transparent pixels

Mode RGB means there is no alpha channel at all. Mode RGBA with every alpha value at 255 means the channel exists but nothing was cut out.

My prompt already says transparent background — why pass the parameter too

A prompt only asks the model to paint it that way, and the model may paint a grey-and-white checkerboard that merely looks transparent — those are still opaque pixels. Only the background: "transparent" parameter guarantees a real alpha channel.

GPT-Image-2 overview

Full parameters, sizes, quality tiers, and error codes

Text-to-image API reference

Every field on /v1/images/generations

Image editing API reference

/v1/images/edits and multi-image fusion

Mask inpainting

Use an alpha mask to mark the region to change

Official vs reverse routes

Choosing between gpt-image-2 / -all / -vip

Artifacts on white backgrounds

A different problem with pure-white backgrounds

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How do I generate images with a transparent background (PNG cutouts)?

Short answer

Which models can produce transparent backgrounds

Three ways to call it

Text-to-image `/v1/images/generations`

Image editing `/v1/images/edits`

Responses image tool

Why `jpeg` does not work

Editing is a re-draw, not a precise cutout

Billing

Common errors

GPT-Image-2 overview

Text-to-image API reference

Image editing API reference

Mask inpainting

Official vs reverse routes

Artifacts on white backgrounds

​Short answer

​Which models can produce transparent backgrounds

​Three ways to call it

​Text-to-image /v1/images/generations

​Image editing /v1/images/edits

​Responses image tool

​Why jpeg does not work

​Editing is a re-draw, not a precise cutout

​Billing

​Common errors

​Related docs

GPT-Image-2 overview

Text-to-image API reference

Image editing API reference

Mask inpainting

Official vs reverse routes

Artifacts on white backgrounds

Short answer

Which models can produce transparent backgrounds

Three ways to call it

Text-to-image `/v1/images/generations`

Image editing `/v1/images/edits`

Responses image tool

Why `jpeg` does not work

Editing is a re-draw, not a precise cutout

Billing

Common errors

Related docs