GPT Image 2.6 Flare Image Edit API

openai/gpt-image-2.6-flare/edit

image_urls · mask_url

GPT Image 2.6 Flare Image Edit turns 1–16 reference images and text instructions into a new 1K–4K image, with optional masks, transparent cutouts and adjustable planning effort. It keeps the first image’s aspect ratio by default, and keep-and-change instructions let it recolor or relight a subject while the rest holds.

Get API Key

Input

PromptRequired517/32000

Image UrlsRequired

Drag and drop files, paste from clipboard, or provide a URL. Provide 1–16 public HTTP(S) image URLs without embedded credentials, in the order the prompt refers to them. Each image adds 2.50 credits to the upfront cap.

1/16 files added

SizeOptional

ResolutionOptional

Output FormatOptional

QualityOptional

BackgroundOptional

ModerationOptional

ComplexityOptional

Mask UrlOptional

Drag and drop files, paste from clipboard, or provide a URL. Optional single public HTTP(S) mask image. Its fully transparent area marks the region of image 1 to change. Masks are free.

OutputReady

Maximum upfront charge: 12.00 credits · $0.06000

Billed by actual tokens. Any difference is refunded after completion.

Continue using

GPT Image 2.6 Flare Text to Image GPT Image 2.6 Sunburst Image Edit GPT Image 2.5 Flare Image Edit

Examples

Use image 1 as the only reference. Isolate the stoneware dripper sitting on the glass carafe of coffee, together with the small cup on its saucer, onto a fully transparent background. Remove the travertine slab, wall, shadows, coffee beans and steam. Keep the speckled glaze, filter paper, glass reflections, coffee color and the relative position of the two objects exactly as in the photo, with clean natural edges. No text, no logos, no watermark.

Edit image 1 using the supplied mask. Replace only the pale overcast sky with a clear early-evening sky: soft gradient from warm apricot near the horizon to light cobalt above, a few thin pink cirrus streaks, and a gentle alpenglow on the snowy summits. Keep the same gouache-and-ink style and brush texture. Keep the mountain outlines, the red train, stone viaduct, larch forest, chalets, chapel and river unchanged. No text, no logos, no watermark.

REST API

Quick Start

This flow submits one valid GPT Image 2.6 Flare Image Edit request, captures its task_id, and reads image URLs after the asynchronous task ends.

Connect to the Vidgo API

Create an API key, keep it on the server, and send it as Authorization: Bearer VIDGO_API_KEY.

Endpoint: POSThttps://api.vidgo.ai/api/generate/submit
Authentication: Authorization: Bearer VIDGO_API_KEY

Submit one image task

Send the current model ID, prompt, and ordered image URLs to the unified submit endpoint. The example keeps only first-call fields.

Submit request

curl --request POST \
  --url "https://api.vidgo.ai/api/generate/submit" \
  --header "Authorization: Bearer $VIDGO_API_KEY" \
  --header "Content-Type: application/json" \
  --data '{
  "model": "openai/gpt-image-2.6-flare/edit",
  "input": {
    "prompt": "Replace the sky with a starry night sky. Keep everything else unchanged.",
    "image_urls": [
      "https://example.com/image.png"
    ],
    "resolution": "1K",
    "output_format": "png",
    "quality": "medium",
    "complexity": "low"
  }
}'

Wait for the image result

Read data.task_id and poll only while status is not_started or running. Stop on both finished and failed.

Track status

GET https://api.vidgo.ai/api/generate/status/{task_id}

Poll every 2–5 seconds and back off on 429/5xx. Or provide top-level callback_url to receive a terminal-state callback.

not_startedrunningfinishedfailed

Submit response

{
  "code": 200,
  "data": {
    "task_id": "task-example",
    "status": "not_started",
    "created_time": "2026-09-25T08:00:00"
  }
}

Finished response

{
  "code": 200,
  "data": {
    "task_id": "task-example",
    "status": "finished",
    "created_time": "2026-09-25T08:00:00",
    "files": [
      {
        "file_url": "https://example.com/result.png",
        "file_type": "image"
      }
    ]
  }
}

Complete runnable polling example

Expand for the same payload end to end, including business-code, missing-task-ID, failed-state, unexpected-state, and network-error handling.

Complete runnable polling example

set -euo pipefail
: "${VIDGO_API_KEY:?Set VIDGO_API_KEY in your environment}"

REQUEST_BODY=$(cat <<'JSON'
{
  "model": "openai/gpt-image-2.6-flare/edit",
  "input": {
    "prompt": "Replace the sky with a starry night sky. Keep everything else unchanged.",
    "image_urls": [
      "https://example.com/image.png"
    ],
    "resolution": "1K",
    "output_format": "png",
    "quality": "medium",
    "complexity": "low"
  }
}
JSON
)

SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  --request POST \
  --url "https://api.vidgo.ai/api/generate/submit" \
  --header "Authorization: Bearer $VIDGO_API_KEY" \
  --header "Content-Type: application/json" \
  --data "$REQUEST_BODY")

TASK_ID=$(printf '%s' "$SUBMIT_RESPONSE" | jq -r '.data.task_id // .task_id // empty')
if [ -z "$TASK_ID" ]; then
  printf 'Submit response did not include task_id:
%s
' "$SUBMIT_RESPONSE" >&2
  exit 1
fi

while true; do
  STATUS_RESPONSE=$(curl --silent --show-error --fail-with-body \
    --url "https://api.vidgo.ai/api/generate/status/$TASK_ID" \
    --header "Authorization: Bearer $VIDGO_API_KEY")
  STATUS=$(printf '%s' "$STATUS_RESPONSE" | jq -r '.data.status // .status // empty')

  case "$STATUS" in
    finished)
      printf '%s' "$STATUS_RESPONSE" | jq -r '(.data.files // .files // [])[]?.file_url'
      break
      ;;
    failed)
      printf '%s' "$STATUS_RESPONSE" | jq -r '.data.error_message // .error_message // "Generation failed"' >&2
      exit 1
      ;;
    not_started|running)
      sleep 2
      ;;
    *)
      printf 'Unexpected task status: %s
' "$STATUS" >&2
      exit 1
      ;;
  esac
done

Request Parameters

This table lists only public fields inside input. See Quick Start for top-level model and optional callback_url usage.

Field	Type	Required	Default	Description
input.prompt	string	Yes	–	Edit instructions, non-blank, up to 32,000 characters. Refer to references by order, such as image 1.
input.image_urls	string[] \| string	Yes	–	Provide 1–16 public HTTP(S) image URLs without embedded credentials, in the order the prompt refers to them. Each image adds 2.50 credits to the upfront cap.
input.size	string	No	Follows image 1	When omitted, the output follows the first reference image's aspect ratio. Ratios: auto, 1:1, 2:3, 3:2, 4:3, 3:4, 4:5, 5:4, 16:9, 9:16, 21:9, or custom WIDTHxHEIGHT. auto works at any resolution and is billed at 1K. Custom WIDTHxHEIGHT works at any resolution: positive multiples of 16, maximum edge 3840, ratio at most 3:1 and 655360–8294400 pixels, billed at the higher of the selected resolution and its pixel tier (up to 1,572,864 px 1K, up to 4,194,304 px 2K, above that 4K).
input.resolution	string	No	1K	1K, 2K or 4K. Default 1K. 1K, 2K, 4K.
input.output_format	string	No	png	png, jpeg or webp. Default png. png, jpeg, webp.
input.quality	string	No	high	low, medium, high, xhigh or max. Default high. Quality and the billing tier set the upfront cap; final billing uses actual tokens. low, medium, high, xhigh, max.
input.background	string	No	auto	auto, transparent or opaque. Default auto. transparent requires png or webp. auto, transparent, opaque.
input.output_compression	integer	No	–	Integer from 0 to 100 for jpeg or webp output. Leave empty for the default compression.
input.moderation	string	No	auto	auto or low. Default auto; low applies less restrictive filtering. Does not change the price. auto, low.
input.complexity	string	No	high	low, medium or high. Default high. Sets how much the model plans before rendering and does not change the price; low suits most edits. low, medium, high.
input.mask_url	string	No	–	Optional single public HTTP(S) mask image. Its fully transparent area marks the region of image 1 to change. Masks are free.

Response Fields

The submit response identifies the task. The status response supplies image files or failure details at a terminal state.

Field	Type	Description
code	integer	Business response code; 0 or 200 indicates success.
message	string	Optional human-readable response message.
data.task_id	string	Unique task ID used for status queries after submission.
data.status	string	not_started, running, finished, or failed.
data.created_time	string	Task creation timestamp.
data.progress	integer	Progress from 0–100 in status responses.
data.files[]	array	Generated files in returned order when finished.
data.files[].file_url	string	Direct generated-image URL.
data.files[].file_type	string	Image results are identified as image.
data.files[].watermark_url	string \| null	Optional watermarked-file URL when present.
data.error_message	string \| null	Readable failure reason for failed tasks.

Task Lifecycle

Only the first two states may be polled again. finished and failed are terminal.

not_started
Accepted and queued; wait before checking again.
running
Image generation is in progress; continue polling.
finished
Successful terminal state; validate files and read image URLs.
failed
Failure terminal state; read error_message and stop.

Polling and Errors

AuthenticationKeep a valid VIDGO_API_KEY on the server and send requests with Bearer authentication.
Validation400 indicates an invalid model ID, field, enum, length, or image count.
Polling intervalStart at 2–5 seconds, use exponential backoff for 429/5xx, and enforce an overall timeout.
Terminal statesRead image URLs from files after finished, or error_message after failed. Both states end polling.
Callback optionProvide a public top-level callback_url to receive a flat task object after finished or failed.
Network errorsDistinguish request timeout, network failure, and task failure. Retry the same query only when safe.

Model Specifications

Specification	Value	Details
Model	openai/gpt-image-2.6-flare/edit	Edit reference images using text instructions.
size	auto / 1:1 / 2:3 / 3:2 / 4:3 / 3:4 / 4:5 / 5:4 / 16:9 / 9:16 / 21:9 / WIDTHxHEIGHT	When omitted, follows the first reference image's aspect ratio.
Output	1 image per request · png / jpeg / webp	jpeg and webp accept output_compression from 0 to 100.
complexity	low / medium / high	Planning effort before rendering. Default high; does not change the price.

GPT Image 2.6 Flare Image Edit API documentation

GPT Image 2.6 Flare Image Edit

GPT Image 2.6 Flare Image Edit uses the faster editing model in OpenAI’s Images 2.6 release from November 2026. It accepts up to 16 ordered reference images and an optional mask for restyling, background swaps, product recolors and multi-image composites. OpenAI recommends lower complexity for most edits, which makes them quicker with fewer unrequested changes, and the output follows the first image’s aspect ratio unless you set size.

Why Choose GPT Image 2.6 Flare Image Edit?

Quick iterative editsFlare is the speed-focused Images 2.6 model, suited to repeated rounds of product, retouching and layout edits.
Lower complexity for focused changesOpenAI recommends low complexity for most edits: the model plans less, finishes sooner and keeps more of the source intact. Every level costs the same.
Up to 16 ordered referencesCombine a scene with products, props or style frames by referring to each image by its order in the prompt.
Aspect ratio follows your sourceLeave size empty and the output uses the preset closest to image 1 at the chosen resolution. Set size only when you need a different frame.
Masks and transparent cutoutsLimit a change to a masked region, or isolate a subject on a transparent PNG or WebP background.
Capped token billingEach reference adds 2.50 credits to the upfront cap. The final charge follows actual tokens, and the rest is refunded.

Parameters

Parameter	Requirement	Description
prompt	Required	Edit instructions, non-blank, up to 32,000 characters. Refer to references by order, such as image 1.
image_urls	Required	Provide 1–16 public HTTP(S) image URLs without embedded credentials, in the order the prompt refers to them. Each image adds 2.50 credits to the upfront cap.
size	Optional	When omitted, the output follows the first reference image's aspect ratio. Ratios: auto, 1:1, 2:3, 3:2, 4:3, 3:4, 4:5, 5:4, 16:9, 9:16, 21:9, or custom WIDTHxHEIGHT. auto works at any resolution and is billed at 1K. Custom WIDTHxHEIGHT works at any resolution: positive multiples of 16, maximum edge 3840, ratio at most 3:1 and 655360–8294400 pixels, billed at the higher of the selected resolution and its pixel tier (up to 1,572,864 px 1K, up to 4,194,304 px 2K, above that 4K). Default`Follows image 1`
resolution	Optional	1K, 2K or 4K. Default 1K. Default`1K2K4K`
output_format	Optional	png, jpeg or webp. Default png. Default`pngjpegwebp`
quality	Optional	low, medium, high, xhigh or max. Default high. Quality and the billing tier set the upfront cap; final billing uses actual tokens. Default`highlowmediumxhighmax`
background	Optional	auto, transparent or opaque. Default auto. transparent requires png or webp. Default`autotransparentopaque`
output_compression	Optional	Integer from 0 to 100 for jpeg or webp output. Leave empty for the default compression.
moderation	Optional	auto or low. Default auto; low applies less restrictive filtering. Does not change the price. Default`autolow`
complexity	Optional	low, medium or high. Default high. Sets how much the model plans before rendering and does not change the price; low suits most edits. Default`highlowmedium`
mask_url	Optional	Optional single public HTTP(S) mask image. Its fully transparent area marks the region of image 1 to change. Masks are free.

How to Use

Add reference imagesUpload 1–16 images or paste public URLs, with the image you want to edit first.
Write keep-and-change instructionsName the one thing that changes, then list what stays: subject, positions, lighting and camera angle.
Add a mask when neededProvide a mask whose transparent area covers the region to change, and describe the new content in the prompt.
Choose size, quality and complexityLeave size empty to keep image 1’s ratio, start at low or medium quality, and set complexity to low for focused edits.
Run and iterateSubmit the task, read the edited image URL when it is finished, and use it as image 1 for the next round.

Usage and Pricing

Billed by actual text input, image input and image output tokens. 1 credit = $0.005.

An upfront cap is held at submission from quality and billing tier, from 5.50 credits at low 1K to 142.34 credits at max 4K, plus 2.50 credits per reference image; masks are free. The cap is the most a task can cost: after completion, actual tokens are settled and the difference is refunded, and failed tasks are refunded in full.

Usage and Pricing
Usage	Credits / 1M tokens	USD / 1M tokens
Text input	800	$4.00
Image input	1,280	$6.40
Image output	4,800	$24.00

Best Use Cases

Product recolors and variantsChange glaze, fabric or finish colors while shape, props and lighting stay put, as in the teal pour-over example.
Cutouts for e-commerce and designRemove backgrounds to transparent PNG or WebP for catalogs, decks and layouts.
Sky and background replacementMask the sky or backdrop and replace it while the foreground keeps its drawing and style.
Multi-image compositesPlace a product or character from one reference into the scene from another.

Pro Tips

Lead with image 1: the first reference is the scene being edited and sets the default aspect ratio.
State what to keep: list the shapes, positions, lighting and camera that must stay, then describe the single change.
Start recolors and cutouts at complexity low; raise it when an edit coordinates many elements.
Pair the mask with a precise prompt: the mask marks where to edit, and the prompt says what to draw there.

Notes

image_urls takes 1–16 public HTTP(S) URLs; mask_url takes one.
Each request returns one image. Omit size to follow image 1’s aspect ratio.
For prompt-only generation, use GPT Image 2.6 Flare Text to Image.
Tasks run asynchronously: submission returns a task_id, and the finished status carries the image URL.

Related Models

GPT Image 2.6 Flare Text to Image preview

GPT Image 2.6 Flare Text to ImageGPT Image 2.6 Flare Text to Image turns text prompts into 1K–4K images with fast low-quality drafts, legible poster typography and transparent backgrounds. It places headlines, subjects and props where the prompt puts them, so one prompt carries a concept from quick draft to final quality.

GPT Image 2.6 Sunburst Text to Image preview

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GPT Image 2.6 Sunburst Image Edit preview

GPT Image 2.6 Sunburst Image EditGPT Image 2.6 Sunburst Image Edit turns 1–16 reference images and text instructions into a refined 1K–4K image, with masks, multi-image composites and quality up to max. Built for stronger consistency across edits, it keeps identity, materials and lighting steady while applying the requested change.

Ideogram Vector 1.0 Text to Vector preview

Ideogram Vector 1.0 Text to VectorIdeogram Vector 1.0 Text to Vector turns a written prompt into SVG artwork for logos, icons and illustrations, with up to five reference images and 17 aspect ratios plus auto. Results are true vector files that scale cleanly from favicon to billboard.

Ideogram Vector 1.0 Image to Vector preview

Ideogram Vector 1.0 Image to VectorIdeogram Vector 1.0 Image to Vector turns one raster image into an SVG file, with a detailed default mode and a simple mode that uses fewer shapes. It follows the shapes and colours of the source so logos, sketches and illustrations become scalable artwork.

FLUX 3 Klein Text to ImageFLUX 3 Klein Text to Image turns prompts into product shots, scenes and illustrations at 1K, 2K or 4K, with seven presets, exact custom sizes and up to four images per call. It keeps per-image cost low so you can iterate widely before rendering finals.

FLUX 3 Klein EditFLUX 3 Klein Edit turns one to ten input images and a written instruction into edited or combined results at 1K, 2K or 4K, priced the same as generation. It keeps the subjects you name from each image while changing backgrounds, outfits, materials or style.

Nano Banana 2.1 Text to ImageNano Banana 2.1 Text to Image turns text prompts into 1K–4K images with text layout rendering and panoramic compositions. It preserves perspective and lighting while eliminating tiling artifacts in panoramic aspect ratios.

Nano Banana 2.1 EditNano Banana 2.1 Edit uses 1–10 reference images for image blending and local edits, with consistent characters and sharp redraws. It preserves character appearance and lighting as elements change, delivering crisp results at up to 4K resolution.

Ideogram 4.5 Text to ImageIdeogram 4.5 Text to Image turns written prompts into posters, wordmarks and text-rich images, with three quality tiers and 1–8 images per request. It keeps headlines and short copy legible while you pick the aspect ratio or one of 36 exact pixel sizes.

Ideogram 4.5 EditIdeogram 4.5 Edit turns one source image and a written instruction into a revised image, with optional masks, up to four reference images and high edit precision. It keeps the areas you did not ask to change, so repeated edits stay close to the original.

Qwen Image 2.1 Text to ImageQwen Image 2.1 Text to Image turns text into native 1K and 2K images with RGBA transparency and Chinese-English typography. It preserves lighting, composition, and aspect ratios while delivering clean transparent layers that need no background removal.

Qwen Image 2.1 EditQwen Image 2.1 Edit turns 1-10 reference images and instructions into precise edits, with multi-image feature fusion and masked inpainting. It preserves facial features and product materials while replacing backgrounds naturally and retaining every pixel outside the mask.

Seedream 5.0 Flash Text to Image preview

Seedream 5.0 Flash Text to ImageSeedream 5.0 Flash Text to Image turns text prompts into high-definition 1K to 2K images, with Chinese and English text layout and 8 aspect ratios. It closely follows complex prompts while providing fine control over lighting and composition.

Seedream 5.0 Flash Image EditSeedream 5.0 Flash Image Edit combines 1 to 10 reference images with a prompt to create new work at up to 2K resolution. It closely preserves faces, clothing and composition from the source images while naturally transforming their style.

GPT Image 2.5 Flare Text to Image preview

GPT Image 2.5 Flare Text to ImageGPT Image 2.5 Flare Text to Image turns text prompts into detailed 1K–4K images, with transparent backgrounds and low latency. It combines fast responses with natural lighting while avoiding structural distortion in large images.

GPT Image 2.6 Flare Image Edit API FAQ

What is the GPT Image 2.6 Flare Image Edit API?

GPT Image 2.6 Flare Image Edit is an OpenAI model for editing images with text instructions. It takes 1–16 reference images and an optional mask and returns one 1K, 2K or 4K image, handling recolors, background swaps, cutouts and multi-image composites with speed-focused turnaround. Part of OpenAI’s Images 2.6 release, it follows the first image’s aspect ratio by default and adds complexity control so edits stay focused on the requested change. You can call it programmatically or try it from the playground above.

Which complexity works best for GPT Image 2.6 Flare Image Edit?

Start with low. OpenAI recommends lower complexity for most edits because the model plans less, finishes sooner and makes fewer unrequested changes; the teal pour-over recolor on this page uses low. Move to medium or high when an edit coordinates many elements. complexity leaves the price unchanged.

Does GPT Image 2.6 Flare Image Edit keep the source aspect ratio?

Yes, when you leave size out. The output uses the preset closest to the first reference image at the selected resolution, which is how the teal pour-over example kept its 4:5 frame. Send a preset, auto or a custom WIDTHxHEIGHT to choose another frame.

How many reference images does GPT Image 2.6 Flare Image Edit accept?

Up to 16 public HTTP(S) image URLs in image_urls. Refer to them by order in the prompt, such as image 1 for the scene and image 2 for the product. Each image adds 2.50 credits to the upfront cap.

How do masks work in GPT Image 2.6 Flare Image Edit?

Send one mask image in mask_url. Its fully transparent area marks the part of image 1 to change, such as the sky in the alpine viaduct example, while the prompt describes the new content. Masks add nothing to the price.

Can GPT Image 2.6 Flare Image Edit remove a background?

Yes. Set background to transparent with png or webp output and ask for the subject isolated on a transparent background. The pour-over cutout example on this page uses webp at low quality.

How is GPT Image 2.6 Flare Image Edit billed?

By actual tokens: 800 credits per 1M text input tokens, 1,280 per 1M image input tokens and 4,800 per 1M image output tokens, with 1 credit = $0.005. The upfront cap is the quality-and-tier price plus 2.50 credits per reference, for example 13.08 credits for one image at high quality and 1K; unused credits are refunded.

Should I use GPT Image 2.6 Flare or Sunburst Image Edit?

Use Flare for fast rounds of recolors, cutouts and background swaps. OpenAI positions Sunburst for more detail and stronger consistency across edits at medium and high quality, which suits final retouching and multi-step edits. Both accept the same fields at the same prices.