50% Lower Latency Than GPT Image 2
OpenAI reports 50% lower latency than GPT Image 2, making Flare the practical default for rapid previews, social assets, product variations, and high-volume image jobs.
GPT Image 2.5 Flare
OpenAI's speed-focused GPT Image 2.5 model for everyday generation and precise editing. Use text or image inputs, choose quality from low through max, and create custom-size images up to 4K with 5% off official token rates on GPTProto.
API 呼叫範例
curl --request POST "https://gptproto.com/api/v3/openai/gpt-image-2.5-flare/text-to-image" \
--header "Authorization: Bearer $GPTPROTO_API_KEY" \
--header "Content-Type: application/json" \
--data '{
"prompt": "A tiny origami fox sailing a teacup across a moonlit puddle",
"n": null,
"quality": "auto",
"size": "auto",
"enable_sync_mode": false,
"response_format": "url"
}'GPT Image 2.5 Flare 定價
先從單次樣本成本開始，再選擇測試預算。GPTProto 費率比標價低 5%。
用量數量單價小計
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相關模型
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| 模型 | 解析度 | 輸入 → 輸出 | ||
|---|---|---|---|---|
| $7.60 / $28.50 每 1M | more | 輸入: 文字輸入: 圖像 輸出: 圖像 | |
| $7.60 / $28.50 每 1M | — | 輸入: 文字輸入: 圖像 輸出: 圖像 | ||
| — | $0.04 / 每次 | 1K · 2K · more | 輸入: 文字輸入: 圖像 輸出: 圖像 | |
| $0.04 / 每次 | 1K · 2K | 輸入: 文字輸入: 圖像 輸出: 圖像 | ||
| $0.02 / 每次 | 1K | 輸入: 文字輸入: 圖像 輸出: 圖像 | ||
| $0.04 / 每次 | 1K · 2K · 4K | 輸入: 文字輸入: 圖像 輸出: 圖像 | ||
| $6.40 / $24.00 每 1M | — | 輸入: 文字輸入: 圖像 輸出: 圖像 | ||
| $0.04 / 每次 | 1K · 2K · 4K | 輸入: 文字輸入: 圖像 輸出: 圖像 | ||
| $0.03 / 每次 | — | 輸入: 文字輸入: 圖像 輸出: 圖像 | ||
| $0.03 / 每次 | — | 輸入: 文字輸入: 圖像 輸出: 圖像 | ||
| $0.01 / 每次 | — | 輸入: 文字輸入: 圖像 輸出: 圖像 | ||
| $0.02 / 每次 | — | 輸入: 文字輸入: 圖像 輸出: 圖像 | ||
| $5.60 / $22.40 每 1M | — | 輸入: 文字輸入: 圖像 輸出: 圖像 | ||
| — | $0.14 / 每次 | — | 輸入: 文字 輸出: 圖像 | |
| $1.75 / $5.60 每 1M | — | 輸入: 文字輸入: 圖像 輸出: 圖像 | ||
| — | $0.01 / 每次 | — | 輸入: 圖像 輸出: 圖像 | |
| — | $0.02 / 每次 | — | 輸入: 圖像 輸出: 圖像 | |
| $0.03 / 每次 | — | 輸入: 文字 輸出: 圖像 | ||
| $0.06 / 每次 | — | 輸入: 文字輸入: 圖像 輸出: 圖像 | ||
| $0.03 / 每次 | — | 輸入: 文字輸入: 圖像 輸出: 圖像 | ||
| $0.05 / 每次 | — | 輸入: 圖像 輸出: 圖像 | ||
| $0.05 / 每次 | — | 輸入: 圖像 輸出: 圖像 | ||
| $0.05 / 每次 | — | 輸入: 文字 輸出: 圖像 | ||
| $7.00 / $28.00 每 1M | — | 輸入: 文字輸入: 圖像 輸出: 圖像 | ||
| $0.06 / 每次 | — | 輸入: 文字輸入: 圖像 輸出: 圖像 |
GPT-Image-2.5 Flare API
Access the OpenAI GPT-Image-2.5 Flare API through GPTProto for fast text-to-image generation and controlled image editing. Flare is the default GPT Image 2.5 choice for most applications, pairing GPT Image 2-class quality with 50% lower latency reported by OpenAI. Use one GPTProto API key and balance at 5% below official token rates.
Precise Edits Without Unwanted Changes
Apply localized edits while retaining the subject, composition, lighting, and visual identity of the source. It is designed to understand both what should change and what should stay fixed.
Custom Image Sizes Up to 4K
Request square, portrait, landscape, or custom dimensions up to 4K. Width and height must be divisible by 16, with supported aspect ratios from 1:3 to 3:1.
What Is the GPT-Image-2.5 Flare API?
GPT-Image-2.5 Flare is OpenAI's smaller, speed-optimized model in the GPT Image 2.5 family. It accepts text and image inputs and returns image outputs for new generation, full-image transformation, and focused edits. OpenAI positions it as the starting point for creator tools, social content, visual search, product experiences, rapid prototyping, and higher-volume workloads.
Flare is more than a faster rerun of GPT Image 2. It improves subject preservation and edit locality, so a request such as “change the jacket to red” is less likely to alter the person's face, pose, framing, or background. It also adds xhigh and max above the earlier model's low, medium, and high quality settings.
The API accepts standard sizes or custom WIDTHxHEIGHT values. Both dimensions must be divisible by 16, and the aspect ratio must stay between 1:3 and 3:1. Resolutions above 2560×1440 are experimental, with 3840×2160 landscape and 2160×3840 portrait as the maximum 4K formats. Transparent outputs require PNG or WebP.
| Specification | GPT-Image-2.5 Flare |
|---|---|
| Provider | OpenAI |
| Model ID | gpt-image-2.5-flare |
| Pinned snapshot | gpt-image-2.5-flare-2026-09-08 |
| Inputs and output | Text + image inputs; image output |
| Supported tasks | Text-to-image generation and image editing |
| Quality | auto, low, medium, high, xhigh, max |
| Size | auto or custom dimensions up to 4K within supported limits |
| Background | auto, opaque, transparent |
| Output formats | PNG, JPEG, WebP |
GPT-Image-2.5 Flare vs GPT Image 2, Sunburst, and Seedream 5 Pro
The right model depends on whether your bottleneck is response time, final-edit precision, or design-specific output. The models below are available within GPTProto, so you can test the same brief without maintaining a separate vendor balance.
| Model | Start with it when | Main advantage | Main trade-off |
|---|---|---|---|
| GPT-Image-2.5 Flare | You need fast drafts, frequent variants, or responsive image features | 50% lower latency than GPT Image 2 reported by OpenAI; six quality modes | Sunburst is the stronger first test for the most demanding final edits |
| GPT-Image-2.5 Sunburst | Edit precision and fine detail outweigh generation time | OpenAI's quality-oriented GPT Image 2.5 tier | Longer generation time than Flare |
| GPT Image 2 | An existing integration already meets its quality and latency targets | Established workflow with generation and editing support | No xhigh or max; slower than Flare according to OpenAI |
| Seedream 5.0 Pro | You need dense multilingual layouts or editable design assets | Design reasoning, high-density text handling, and layer separation | Different prompting and API conventions from GPT Image models |
For a current GPT Image 2 workflow, keep the prompt, reference images, size, format, and quality fixed, then test Flare first. Move the same request to Sunburst only when Flare misses a quality requirement. Choose Seedream 5.0 Pro when layer separation or multilingual layout work is central to the deliverable.
GPT-Image-2.5 Flare Prompt Guide for Fast Iteration
Flare works best when a prompt separates the requested change from the elements that must remain stable. For generation, state the deliverable, composition, subject, text, and output constraints in that order. For editing, use a three-part instruction: change, preserve, and output.
Fast product variation:
Create a square ecommerce image of the supplied running shoe on pale gray concrete. Generate a soft morning shadow and a clean off-white background. Preserve the product shape, logo placement, materials, and exact color. No extra objects or text.
Localized edit:
Change only the jacket from navy to rust red. Preserve the person's face, hair, pose, hands, camera angle, lighting, background, and crop. Return a 1536×1024 JPEG.
When producing a batch, vary one factor at a time—such as background color, camera angle, or headline—so rejected outputs reveal whether the problem came from the prompt, the reference, or the model. Use medium for early iteration and move to high, xhigh, or max only after the composition is approved.
Access GPT-Image-2.5 Flare on GPTProto
GPTProto provides GPT-Image-2.5 Flare API access through one account, key, and prepaid balance shared with other supported image, video, and language models. Select gpt-image-2.5-flare for the moving model alias or pin gpt-image-2.5-flare-2026-09-08 when repeatable behavior matters. GPTProto applies a 5% discount to the official token rates; actual per-image cost still varies with prompt length, image inputs, output size, and quality.
Who Should Choose gpt-image-2.5-flare for Text to Image
Who Should Choose gpt-image-2.5-flare for Text to Image?
The gpt-image-2.5-flare API text to image workflow is designed for users who demand both creative flexibility and structural reliability. It is an ideal solution for:
- Digital Agencies: Teams needing to produce high-quality storyboards and mockups quickly using gpt-image-2.5-flare.
- Game Developers: Creators requiring rapid generation of environmental assets and textures based on specific thematic prompts.
- Product Designers: Professionals looking to visualize product concepts with high textural accuracy using the gpt-image-2.5-flare engine.
Pro Tips for Using gpt-image-2.5-flare for Text to Image
- Prioritize subject clarity in your prompt; place the primary focus at the beginning of your text string for gpt-image-2.5-flare to process.
- Use specific lighting and lens descriptors to guide the gpt-image-2.5-flare model toward the desired aesthetic result.
- When specifying style, combine artistic medium descriptors with technical lighting terms for more predictable outcomes.
- Iterate on small prompt changes; gpt-image-2.5-flare responds well to subtle adjustments in phrasing to fine-tune composition.
FAQ
Is GPT-Image-2.5 Flare an official OpenAI API model?
Yes. OpenAI released Flare as the smaller, speed-oriented member of the GPT Image 2.5 API family. The official model IDs are gpt-image-2.5-flare and the pinned gpt-image-2.5-flare-2026-09-08 snapshot.
How much faster is GPT-Image-2.5 Flare than GPT Image 2?
OpenAI reports 50% lower latency while positioning Flare at GPT Image 2-class or better quality. Treat that figure as a launch-level comparison: your result will depend on input images, dimensions, quality, prompt complexity, and traffic conditions.
How much does the GPT-Image-2.5 Flare API cost on GPTProto?
GPTProto charges 95% of OpenAI's listed token rates: $4.75 per million text input tokens, $1.1875 cached text input, $7.60 image input, $1.90 cached image input, and $28.50 image output. Image cost is not a fixed per-call amount because token usage varies.
Does GPT-Image-2.5 Flare support image-to-image editing?
Yes. It accepts image inputs for transformations and precise edits. Explicitly name the requested change and list the subject, framing, lighting, or objects that must remain unchanged.
Can GPT-Image-2.5 Flare generate transparent PNGs?
Yes. Set the background to transparent and use PNG or WebP as the output format. Transparent-background generation is useful for product cutouts, interface assets, stickers, and design elements.
GPT-Image-2.5 Flare vs Sunburst: which should I use?
Start with Flare for most applications and latency-sensitive workflows. Use Sunburst when a complex edit or premium final asset does not meet its acceptance criteria on Flare and the additional generation time is acceptable.
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