models

GPT Image 2.5 Flare 2026-09-08

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GPT Image 2.5 Flare 2026-09-08

GPT Image 2.5 Flare is intended for everyday image generation from descriptions. Provides custom sizes, an extended set of quality levels and transparent backgrounds.

About the model

This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.

Everyday generation from text descriptions

GPT Image 2.5 Flare is an OpenAI model for creating images. According to the manufacturer, its purpose is fast everyday generation of high-quality visual material. A prompt can describe the subject, style, detail placement and desired frame shape; the result is an image.

In Ailoot, this card presents generation with text input. OpenAI also describes work with source images, references and edits. These methods require image-input support; they do not mean that the text method already accepts such material.

Quality from a draft to a detailed image

The levels low, medium, high, xhigh, max and automatic selection with auto are supported. Quality affects the amount of work performed when forming the result. It is specified separately from frame size and compression of the finished file.

Square, landscape and portrait size options, automatic selection and custom sizes are provided. Aspect ratios can be selected to suit a composition while meeting all manufacturer limits.

Custom sizes

Each dimension must be a multiple of 16 pixels and no longer than 3840 pixels. The ratio of the longer dimension to the shorter must not exceed 3:1. Permitted area is between 655,360 and 8,294,400 pixels. The limits apply together: a permitted aspect ratio does not remove the area limit.

Resolutions above 2560x1440 are designated as experimental. When selecting a large frame, the composition itself matters: more pixels do not guarantee correct placement of every element.

Output file and transparency

The model provides PNG, JPEG and WebP, with PNG as the standard format. Compression can be controlled for JPEG and WebP. A transparent background requires PNG or WebP. The manufacturer also supports an opaque background and automatic selection. Transparency allows an image to be used in a later composition without a specified backdrop.

Manufacturer settings describe model capabilities; execution depends on parameter support in the selected method. A separate generation creates a new result, so an identical description does not guarantee that images match completely.

What to check in the finished image

According to OpenAI, a complex prompt may take up to two minutes to process. This describes generation with the manufacturer, not a guarantee of total result-delivery time in a particular application.

Text, precise object placement and preservation of one appearance across images need checking. A mask in a separately supported editing operation guides the change rather than imposing a hard boundary. For text-to-image generation, it is useful to describe the composition precisely and inspect the file itself: visible details, readability and conformity to the specified subject.

Ailoot · Images POST /v1/images/generations gpt-image-2.5-flare-2026-09-08

gpt-image-2.5-flare-2026-09-08

OpenAI /gpt-image-2.5-flare-2026-09-08

Overview

GPT Image 2.5 Flare is intended for everyday image generation from descriptions. Provides custom sizes, an extended set of quality levels and transparent backgrounds.

Accepted inputs
Text
Results
Images

Available in Ailoot · inputs & methods

Ailoot · Images POST /v1/images/generations
Input types
text
Output types
image
Output format
Image file
FieldTypeRequirementValues & limitsDefault
FieldmodelTypestringRequirementRequiredValues & limits
gpt-image-2.5-flare-2026-09-08
Default—
FieldpromptTypestringRequirementRequiredValues & limits
Minimum length: 1
Default—
FieldnTypeintegerRequirementOptionalValues & limits
Minimum: 1
Default1
Fieldresponse_formatTypestringRequirementOptionalValues & limits
url, b64_json
Default—
FieldstreamTypebooleanRequirementOptionalValues & limitsDefaultfalse
FieldsizeTypestringRequirementOptionalValues & limits
Model-specific
Default—
FieldqualityTypestringRequirementOptionalValues & limits
Model-specific
Default—
FieldbackgroundTypestringRequirementOptionalValues & limits
Model-specific
Default—
Fieldoutput_formatTypestringRequirementOptionalValues & limits
Model-specific
Default—
Fieldoutput_compressionTypeintegerRequirementOptionalValues & limits
Model-specific
Default—
FieldmoderationTypestringRequirementOptionalValues & limits
Model-specific
Default—
Fieldinput_fidelityTypestringRequirementOptionalValues & limits
Model-specific
Default—
FieldstyleTypestringRequirementOptionalValues & limits
Model-specific
Default—
Fieldpartial_imagesTypeintegerRequirementOptionalValues & limits
Model-specific
Default—
Input material combinations

Text to image · Required: prompt

Method parameters and lifecycle
ParameterContract
Parametermaterial_typesContracttext
ParameterrequiredContractmodel, prompt
Parameteroptional_controlsContractnull
Parametercontent_typeContractapplication/json

Lifecycle: synchronous_result_then_owned_library

GET /v1/media/tasks/{task_id} · actual returned task_id or media library record

GET /v1/media/assets/{asset_id}/content

GET /v1/media/assets

GET /v1/media/assets/{asset_id}

Method shapes and IDs are exact; supplier capability is separate from admission.

Pricing

Ailoot method rates

Ailoot ImagesPOST /v1/images/generations
Text input
$0.005 / 1K
Image input
$0.008 / 1K tokens
Image output
$0.03 / 1K tokens

Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. How reservation and settlement work →

Example requests

Ailoot · Images

curlPython SDKNode.js SDK
set -eu
: "${AILOOT_API_KEY:?Set your Ailoot API key}"
export AILOOT_API_KEY
export AILOOT_API_KEY
: "${AILOOT_PROMPT_FILE:?Set your actual UTF-8 image brief}"
export AILOOT_PROMPT_FILE
python3 - <<'PY_REQUEST'
import json,os
from pathlib import Path
p=json.loads('{"model": "gpt-image-2.5-flare-2026-09-08", "prompt": ""}')
f=Path(os.environ["AILOOT_PROMPT_FILE"])
if not f.is_file():raise SystemExit("Choose your actual UTF-8 brief")
p['prompt']=f.read_text(encoding="utf-8")
if not p['prompt'].strip():raise SystemExit("Brief must contain text")
Path("request.json").write_text(json.dumps(p,ensure_ascii=False))
PY_REQUEST
curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/images/generations \
  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \
  --data-binary @request.json -D response-headers.txt -o result.json
python3 - <<'PY_RESULT'
import base64, json, os, subprocess
from pathlib import Path
from urllib.parse import urlsplit, urljoin

def save_images(items):
    if not items: raise SystemExit("No completed images; retain the full response")
    for index, item in enumerate(items):
        encoded=item.get("b64_json")
        uri=item.get("url", "")
        if not encoded and uri.startswith("data:image/"):
            header, separator, encoded=uri.partition(",")
            if not separator or ";base64" not in header: raise SystemExit("Unsupported image data URI")
        if encoded:
            raw=base64.b64decode(encoded,validate=True)
        elif uri:
            uri=urljoin("https://api.ailoot.ai",uri)
            parsed=urlsplit(uri)
            if parsed.scheme!="https" or not parsed.netloc or parsed.username or parsed.password:
                raise SystemExit("Invalid returned image URL")
            owned=parsed.netloc=="api.ailoot.ai" and parsed.path.startswith("/v1/media/assets/") and parsed.path.endswith("/content")
            args=["curl","--fail-with-body","--silent","--show-error",uri]
            if owned: args += ["-H","Authorization: Bearer "+os.environ["AILOOT_API_KEY"]]
            temporary=Path(f"image-{index}.bin")
            subprocess.run(args+["-o",str(temporary)],check=True)
            raw=temporary.read_bytes()
            temporary.unlink()
        else: raise SystemExit("Image has neither bytes nor URL")
        if not raw: raise SystemExit("Empty image result")
        ext="png" if raw.startswith(b"\x89PNG") else "jpg" if raw.startswith(b"\xff\xd8") else "webp" if raw[:4]==b"RIFF" and raw[8:12]==b"WEBP" else "svg" if raw.lstrip().startswith((b"<svg",b"<?xml")) else "bin"
        Path(f"image-{index}.{ext}").write_bytes(raw)
    print("Every returned image saved; complete response metadata retained")
save_images(json.loads(Path("result.json").read_text())["data"])
PY_RESULT
from openai import OpenAI
import base64, json, os, subprocess
from pathlib import Path
from urllib.parse import urlsplit, urljoin

def save_images(items):
    if not items: raise SystemExit("No completed images; retain the full response")
    for index, item in enumerate(items):
        encoded=item.get("b64_json")
        uri=item.get("url", "")
        if not encoded and uri.startswith("data:image/"):
            header, separator, encoded=uri.partition(",")
            if not separator or ";base64" not in header: raise SystemExit("Unsupported image data URI")
        if encoded:
            raw=base64.b64decode(encoded,validate=True)
        elif uri:
            uri=urljoin("https://api.ailoot.ai",uri)
            parsed=urlsplit(uri)
            if parsed.scheme!="https" or not parsed.netloc or parsed.username or parsed.password:
                raise SystemExit("Invalid returned image URL")
            owned=parsed.netloc=="api.ailoot.ai" and parsed.path.startswith("/v1/media/assets/") and parsed.path.endswith("/content")
            args=["curl","--fail-with-body","--silent","--show-error",uri]
            if owned: args += ["-H","Authorization: Bearer "+os.environ["AILOOT_API_KEY"]]
            temporary=Path(f"image-{index}.bin")
            subprocess.run(args+["-o",str(temporary)],check=True)
            raw=temporary.read_bytes()
            temporary.unlink()
        else: raise SystemExit("Image has neither bytes nor URL")
        if not raw: raise SystemExit("Empty image result")
        ext="png" if raw.startswith(b"\x89PNG") else "jpg" if raw.startswith(b"\xff\xd8") else "webp" if raw[:4]==b"RIFF" and raw[8:12]==b"WEBP" else "svg" if raw.lstrip().startswith((b"<svg",b"<?xml")) else "bin"
        Path(f"image-{index}.{ext}").write_bytes(raw)
    print("Every returned image saved; complete response metadata retained")

f=Path(os.environ["AILOOT_PROMPT_FILE"])
if not f.is_file():raise SystemExit("Set your actual UTF-8 image brief file")
request={'model': 'gpt-image-2.5-flare-2026-09-08', 'prompt': ''}
request["prompt"]=f.read_text(encoding="utf-8")
client=OpenAI(base_url="https://api.ailoot.ai/v1",api_key=os.environ["AILOOT_API_KEY"],max_retries=0)
result=client.images.generate(**request)
Path("sdk-result.txt").write_text(str(result),encoding="utf-8")
save_images([{"b64_json":getattr(item,"b64_json",None),"url":getattr(item,"url",None)} for item in result.data])
import OpenAI from "openai";
import { readFileSync, writeFileSync } from "node:fs";
const key=process.env.AILOOT_API_KEY;
if(!key) throw new Error("Set your actual Ailoot API key");
const client=new OpenAI({baseURL:"https://api.ailoot.ai/v1",apiKey:key,maxRetries:0});
const request={"model": "gpt-image-2.5-flare-2026-09-08", "prompt": ""};
if(!process.env.AILOOT_PROMPT_FILE)throw new Error("Set your actual UTF-8 image brief file");
request.prompt=readFileSync(process.env.AILOOT_PROMPT_FILE,"utf8");
const result=await client.images.generate(request);
writeFileSync("sdk-result.json",JSON.stringify(result,null,2));
if(!result.data?.length) throw new Error("No completed images");
for(let index=0;index<result.data.length;index++) {
  const item=result.data[index];let encoded=item.b64_json,uri=item.url||"",raw;
  if(!encoded && uri.startsWith("data:image/")) {
    const comma=uri.indexOf(",");if(comma<0 || !uri.slice(0,comma).includes(";base64")) throw new Error("Unsupported image data URI");
    encoded=uri.slice(comma+1);
  }
  if(encoded) {
    if(encoded.length%4!==0 || !/^[A-Za-z0-9+/]*={0,2}$/.test(encoded)) throw new Error("Invalid Base64");
    raw=Buffer.from(encoded,"base64");
  } else if(uri) {
    const u=new URL(uri,"https://api.ailoot.ai");
    if(u.protocol!=="https:" || u.username || u.password) throw new Error("Invalid returned URL");
    const owned=u.origin==="https://api.ailoot.ai" && u.pathname.startsWith("/v1/media/assets/") && u.pathname.endsWith("/content");
    const response=await fetch(u,{headers:owned?{Authorization:"Bearer "+key}:{},redirect:"manual"});
    if(!response.ok) throw new Error("Image content download failed: "+response.status);
    raw=Buffer.from(await response.arrayBuffer());
  } else throw new Error("Image has neither bytes nor URL");
  if(!raw.length) throw new Error("Empty image result");
  const ext=raw.subarray(0,4).equals(Buffer.from([137,80,78,71]))?"png":raw[0]===255&&raw[1]===216?"jpg":raw.toString("ascii",0,4)==="RIFF"&&raw.toString("ascii",8,12)==="WEBP"?"webp":raw.toString("utf8").trimStart().startsWith("<svg")||raw.toString("utf8").trimStart().startsWith("<?xml")?"svg":"bin";
  writeFileSync(`image-${index}.${ext}`,raw);
}
console.log("Every returned image saved; sdk-result.json retains complete metadata");

Receive and save results

Ailoot · Images

Download each returned image or save its Base64 contents

  • GET /v1/media/tasks/{task_id}
  • GET /v1/media/assets/{asset_id}/content
  • GET /v1/media/assets
  • GET /v1/media/assets/{asset_id}
Keep all completed results

Save every completed image; retrieve each returned URL or decode its Base64 contents.

Save every data item. Decode each b64_json or fetch every returned signed URL. Select a filename extension from the actual MIME/bytes.

If the original response needs checking

If an image generation or edit result requires a check, keep the original operation_id/X-Client-Request-ID and returned result information. Recover existing owned results through the media library using actual task_id or asset_id values. Do not resubmit the generation/edit request or construct a polling URL from operation_id.

Response fields
FieldType
FieldcreatedTypeinteger
Fielddata[].urlTypestring
Fielddata[].b64_jsonTypebase64 string
FieldusageTypeobject
Errors and next steps
ResponseConditionNext step
Response400 · invalid_request_errorConditionInvalid required fields, material representation or parameter valueNext stepCorrect the indicated fields before a new creation request.
Responseserver_errorConditionThe returned response says the operation or result requires a checkNext stepKeep the original returned operation/task ID, request headers and response; continue supported reads of that original operation. Do not resubmit the creation request.

Aliases

Model aliases

Ailoot gpt-image-2.5-flare-2026-09-08

Method path aliases

Use the method paths shown above.

Related caller IDs

gpt-image-2.5-flare-2026-09-08

FAQ · GPT Image 2.5 Flare 2026-09-08
What inputs and results are available?

POST /v1/images/generations · gpt-image-2.5-flare-2026-09-08: text → image

Which fields does the request use?

POST /v1/images/generations · gpt-image-2.5-flare-2026-09-08: model, prompt, n, response_format, stream

What limits apply?

POST /v1/images/generations · gpt-image-2.5-flare-2026-09-08: n.minimum: 1

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