OpenAIOpenAI Fast image generation & editing

GPT Image 2.5 Flare

Iterate quickly when the next visual decision matters most.

GPT Image 2.5 Flare is an OpenAI image route positioned for faster high-quality generation and editing. The TokenHot catalog lists text and reference-image input, image output and a 400K context value. Use it for creator content, product experiences, visual search, rapid prototypes and repeated generation where iteration speed is part of the quality loop.

  • Text + image input
  • Image output
  • Fast iteration

Fast iteration does not remove the need for visual QA. Confirm reference-input behavior, size options and output handling in the existing playground or API request before automating publication.

Try this model

Choose an aspect ratio and resolution to generate an image.

gpt-image-2.5-flare

Input

Reference image (optional)

JPG / PNG · Up to 10 MB. Uploaded when you generate.

Aspect ratio
Resolution

1024 × 1024 px

Uses your account balance at the model’s current rates.

Generated result

Your creation appears here

Enter a prompt, choose your settings, and generate.

USD /image

Pricing

GroupPrice
default$0.048
default
$0.048

Public list prices are shown in USD. Final charges may vary by account group and usage tier.

Overview

What is GPT Image 2.5 Flare?

Flare works well when a team needs many candidate directions and can select with a consistent review checklist. Keep each prompt focused, then compare accepted variants rather than choosing from a single lucky output.

Use Sunburst when a change needs tighter editing control and the extra wait is justified. Treat that distinction as a measurable workflow choice, not an absolute quality ranking.

Iteration

Make each turn count

Change one visual variable at a time so the team can understand why a candidate was accepted.

Creator workflows

Design for a feed or product surface

Name dimensions, safe areas and brand constraints before generating a batch.

Editing

Keep references explicit

State the reference image, the requested change and the details that must not drift.

From brief to deliverable

Put GPT Image 2.5 Flare to work

Start with a concrete task and decide what a useful result looks like.

Creative and product teams

Explore several visual directions

Generate a small set of concept directions from the same brief, then select using a rubric for composition, audience fit and production effort.

Tools you need
Image generation, asset versioning and a human reviewer.
Keep in mind
Candidate quantity is not quality; keep the rubric and rejected reasons visible.
View a task brief

Use the supplied a brief, reference, aspect ratio, brand constraints and selection rubric. to plan explore several visual directions. Return a shortlist of viable visual directions., state the evidence limits and list the checks required before accepting the result. Do not claim an output or interaction was verified without direct evidence.

Marketing and content teams

Prepare a social asset batch

Create variants for a defined set of placements while preserving the subject and message hierarchy.

Tools you need
Image generation, storage and an export pipeline.
Keep in mind
Crop, text and small details can fail differently across ratios; inspect each placement.
View a task brief

Use the supplied approved base art, placement sizes, copy-safe areas and a batch manifest. to plan prepare a social asset batch. Return a reviewed asset batch with export metadata., state the evidence limits and list the checks required before accepting the result. Do not claim an output or interaction was verified without direct evidence.

Product design teams

Prototype a product experience

Use a product reference to explore backgrounds, lighting and interface scenes before commissioning final art.

Tools you need
Reference upload, design review and a handoff document.
Keep in mind
Prototype imagery is not a verified product render or a substitute for brand approval.
View a task brief

Use the supplied product image, scene constraints, target surface and rejection criteria. to plan prototype a product experience. Return a selected prototype plus follow-up art direction., state the evidence limits and list the checks required before accepting the result. Do not claim an output or interaction was verified without direct evidence.

Capabilities in context

Key features

FeatureWhat you getWhy it matters
Reference editingText and image input are listedKeep the reference and invariant list attached to each candidate so comparisons are fair.
Image outputThe route returns generated imagesSeparate candidate, selected, reviewed and exported states in your content workflow.
Iteration positioningCatalog copy favors faster iteration and high-volume generationMeasure time to an accepted result rather than speed of the first response alone.
Context capacity400K tokens shown in the catalogKeep image prompts concise and use a batch manifest for repeated constraints.
Pricing unitCatalog billing unit: imageRead the current dynamic rate for the selected account group and size configuration.

The page uses TokenHot catalog metadata and the existing image route. Faster iteration should be evaluated with a visual acceptance rubric and real references.

Audience & fit

Where GPT Image 2.5 Flare fits

Creators and social teams

Use Flare to explore and refresh visual directions quickly while preserving placement and brand constraints.

Product teams

Prototype scenes and visual surfaces before a final art pass, keeping the difference between prototype and approved asset explicit.

High-volume content workflows

Batch by a stable manifest, validate dimensions and inspect every output that carries customer-facing text.

Cost context

Plan the cost of a useful result

Measure time to accepted asset

Include selection, reruns, export and review. A fast generation call can still be expensive if most candidates are rejected.

Price each placement

Image dimensions and account groups can affect the rate. Keep the batch manifest beside the quote.

Protect production details

Review text, logos, faces and product geometry before an image reaches a customer-facing surface.

Use the current pricing table for available rates and account groups. Model IDs and prices come from TokenHot’s catalog; provider pricing and subscriptions are separate.

API

Code examples

curl --location --request POST 'https://api.tokenhot.ai/v1/images/generations' \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data-raw '{
    "model": "gpt-image-2.5-flare",
    "prompt": "A cute baby sea otter",
    "size": "1024x1024"
}'

OpenAI

Related models

OpenAIOpenAIGPT Image 2.5 Sunburst

Built for premium visual workflows where editing precision and finished-image quality matter most: a better fit for production campaign creative, polished product imagery, and multi-turn edits that need to preserve the subject, composition, and visual treatment. It accepts text and reference-image inputs and produces images, with longer generation times than Flare.

$0.048/imageOpenAIOpenAIGPT Image 2

Built for high-quality image generation and editing, improving over GPT Image 1.x in text rendering, local editing, and multi-turn consistency. Compared with Gemini image models, Qwen Image, and Seedream, it is well suited to brand visuals, ad design, product imagery, and tightly controlled creative workflows.

$0.028/imageOpenAIOpenAIGPT Image 2.5 Sunburst Sale

The discounted-price route for GPT Image 2.5 Sunburst, mapped by the current channel to Sunburst. Sale indicates a special-price route and does not change Sunbursts role in high-precision image generation and editing. Best for cost-sensitive professional visual work that still needs reference-image editing and detail control; use regular gpt-image-2.5-sunburst when you want the standard route.

$0.008/imageOpenAIOpenAIGPT Image 2.5 Flare Sale

The discounted-price route for GPT Image 2.5 Flare, mapped by the current channel to Flare. Sale indicates a special-price route and does not change Flares role in fast, high-quality everyday image generation and editing. Best for cost-sensitive, frequent image tasks; use regular gpt-image-2.5-flare when you want the standard route.

$0.008/image

Blog

Related Articles

GPT Image 2 API: Generate, Edit, and Save Images in Python

Use Tokenhot's GPT Image 2 routes from Python to generate an image, edit from a reachable image URL, and save each result with a response-first workflow.

2026-09-24

FAQ

Frequently asked questions

What is GPT Image 2.5 Flare best suited for?

GPT Image 2.5 Flare is suited to the input, output, and capability types listed on this page. Test production workloads before choosing it for a critical system.

How is GPT Image 2.5 Flare priced?

Pricing is shown in the pricing section above. Actual cost depends on usage volume, account group, and the request payload.

How can I call GPT Image 2.5 Flare?

Use the model ID shown above with one of the supported API protocols. Code examples are provided when usage data is available.

Can Flare use a reference image?

The catalog lists text and image input and the existing image workflow supports reference input for this family. Verify the request shape for your selected endpoint.

Should I always use Flare instead of Sunburst?

No. Compare accepted edit fidelity, iteration time and total cost on the same references. Flare is positioned for faster iteration; Sunburst for tighter control.

Can I publish the first generated image?

Treat it as a candidate until visual, brand, text and export checks pass.

How is image pricing calculated?

TokenHot supplies image pricing dynamically. Review the current table for the account group and parameters used by the request.

Get started

Build with GPT Image 2.5 Flare

Use in Console