2K Output & Mask Editing
Native output up to 2K (2048px) with neutral, accurate color — the warm cast from gpt-image-1.5 is gone. Inpaint or outpaint precise regions via mask images while untouched pixels stay pixel-identical.
GPT Image 2
gpt-image-2 is OpenAI's April 2026 image model: agentic "thinking" that plans composition before rendering, native 2K output, multilingual in-image text (including CJK), and mask-based editing with up to 16 reference images. Route it through GPTProto with the standard OpenAI request shape.
API Usage Examples
curl --request POST "https://gptproto.com/api/v3/openai/gpt-image-2/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",
"response_format": "url"
}'GPT Image 2 pricing
Start from the cost of a single sample and pick a testing budget. GPTProto rates are 20% below list price.
UsageQuantityRateCost
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Related Models
All Models
| Model | Resolution | Input → Output | ||
|---|---|---|---|---|
| $6.40 / $24.00 per 1M | more | Input: TextInput: Image Output: Image | |
| $0.04 per time | 1K · 2K | Input: TextInput: Image Output: Image | ||
| $0.02 per time | 1K | Input: TextInput: Image Output: Image | ||
| $0.04 per time | 1K · 2K · 4K | Input: TextInput: Image Output: Image | ||
| $0.04 per time | 1K · 2K · 4K | Input: TextInput: Image Output: Image | ||
| $0.03 per time | — | Input: TextInput: Image Output: Image | ||
| $0.03 per time | — | Input: TextInput: Image Output: Image | ||
| $0.01 per time | — | Input: TextInput: Image Output: Image | ||
| $0.02 per time | — | Input: TextInput: Image Output: Image | ||
| $5.60 / $22.40 per 1M | — | Input: TextInput: Image Output: Image | ||
| — | $0.14 per time | — | Input: Text Output: Image | |
| $0.04 per time | — | Input: Text Output: Image | ||
| $1.75 / $5.60 per 1M | — | Input: TextInput: Image Output: Image | ||
| — | $0.01 per time | — | Input: Image Output: Image | |
| — | $0.02 per time | — | Input: Image Output: Image | |
| $0.03 per time | — | Input: Text Output: Image | ||
| $0.06 per time | — | Input: TextInput: Image Output: Image | ||
| $0.03 per time | — | Input: TextInput: Image Output: Image | ||
| $0.05 per time | — | Input: Image Output: Image | ||
| $0.05 per time | — | Input: Image Output: Image | ||
| $0.05 per time | — | Input: Text Output: Image | ||
| $7.00 / $28.00 per 1M | — | Input: TextInput: Image Output: Image | ||
| $0.06 per time | — | Input: TextInput: Image Output: Image |
GPT Image 2 API
Call OpenAI's gpt-image-2 through one GPTProto key at $6.4/$24 per 1M tokens — 20% under OpenAI's list. Same model ID, no organization verification, one balance shared across 200+ models.
Reference-Guided Consistency
Pass up to 16 reference images in a single call to hold subject identity, style, and product details across a set — for sequential art, catalog shots, and brand-consistent campaigns.
In-Image Text Rendering
Renders small labels, UI copy, and long passages in Latin and CJK scripts with layout accuracy — usable in client work without a separate typesetting pass. A core reason to reach for the gpt image 2 api over older generators.
Agentic Thinking Mod
Before rendering, gpt-image-2 reasons through layout and constraints — the first OpenAI image model with O-series-style planning. It raises success rates on dense scenes like infographics, multi-panel layouts, and packaging.
What Is GPT Image 2?
gpt-image-2 is OpenAI's image generation and editing model, released April 21, 2026 as the successor to gpt-image-1 (April 2025) and gpt-image-1.5 (December 2025). It is natively multimodal — image generation is part of the core model rather than a diffusion model bolted onto a language model — which is why it follows long, multi-part prompts and renders readable in-image text more reliably than DALL-E-era generators.
Two things set the model apart at the API level. First, an agentic "thinking" pass: for complex prompts it plans composition and reasons through constraints before generating, which lifts success rates on infographics, multi-panel layouts, and text-heavy marketing assets. Second, an editing endpoint that accepts mask images for precise inpainting and outpainting, plus up to 16 reference images per call for identity and style consistency. Output is PNG at up to 2K native resolution, with neutral color that fixes the warm cast in gpt-image-1.5.
On GPTProto you call the same gpt-image-2 model ID through the standard OpenAI-compatible request shape — no separate OpenAI account, no organization verification step, and one balance that also covers Nano Banana Pro, Seedream, Flux, and 200+ other models.
GPT Image 2 Specifications
| Spec | GPT Image 2 |
|---|---|
| Model ID | gpt-image-2 |
| Released | April 21, 2026 |
| Type | Text-to-image + image editing (inpaint / outpaint) |
| Output format | PNG (raster) |
| Max resolution | Native 2K (2048px); high-res variants up to ~4K |
| In-image text | Latin + CJK (Chinese / Japanese / Korean), dense layouts |
| Reasoning | Agentic "thinking mode" (plans before rendering) |
| Reference images | Up to 16 per call |
| Editing | Mask-based inpaint / outpaint; unedited pixels preserved |
| Input modality | Text (+ reference images) |
| OpenAI list price | $8 / $30 per 1M tokens (input / output) |
| GPTProto price | $6.4 / $24 per 1M tokens (20% under list) |
| Access | One GPTProto key, no OpenAI org verification |
GPT Image 2 vs Nano Banana Pro (and gpt-image-1.5)
| GPT Image 2 | Nano Banana Pro | GPT Image 1.5 | |
|---|---|---|---|
| Model ID | gpt-image-2 |
gemini-3-pro-image-preview |
gpt-image-1.5 |
| Vendor | OpenAI | OpenAI | |
| Released | Apr 2026 | Nov 2025 | Dec 2025 |
| Max resolution | 2K native (~4K variants ) | up to 4K (4096px) | 2K |
| In-image text | Latin + CJK | multilingual, long passages | improved vs gpt-image-1 |
| Reasoning | agentic thinking | Gemini 3 reasoning + Search grounding | none |
| Reference inputs | up to 16 images | multi-image, ~5-subject identity | fewer |
| OpenAI/Google list | $8 / $30 per 1M | $2 / $12 per 1M | $8 / $32 per 1M |
| GPTProto price | $6.4 / $24 per 1M | $ 0.0804/ per time |
$ 5.6 / $ 22.4 per 1M |
| On GPTProto | ✓ | ✓ | ✓ |
Which to pick (honest): Nano Banana Pro has the lower token rate, native 4K, and Search-grounded generation — reach for it when cost, 4K infographics, or real-world-grounded visuals matter most. GPT Image 2 leads on agentic layout planning, up to 16 reference images, and tight drop-in compatibility with the OpenAI SDK — reach for it for reference-heavy product/packaging work already wired to OpenAI. Because both run on one GPTProto balance, you can benchmark them against your own prompts without opening a second account.
Switching from the Official OpenAI API
If you already call gpt-image-2 on OpenAI, moving to GPTProto is a base-URL swap — the model ID and request shape stay the same:
- Keep
model: "gpt-image-2"and your existingimages.generate/ edit request body. - Point the client at GPTProto's OpenAI-compatible base URL
https://gptproto.com/v1and use your GPTProto key. - Skip OpenAI's Organization Verification gate that fronts the GPT Image family, and skip a second billing account — the same balance covers 200+ models.
gpt image 2 api: Common Questions
Find technical details and usage tips for the gpt image 2 api to enhance your creative workflow and image quality.
How much does the GPT Image 2 API cost?
On GPTProto, gpt-image-2 is $6.4 / $24 per 1M input / output tokens — 20% under OpenAI's $8 / $30 list. Billing draws from one shared balance, so the same key also runs Nano Banana Pro, Seedream, and 200+ other models.
How do I get a GPT Image 2 API key?
Create a free GPTProto account, add credits, and generate a key in the dashboard — it authenticates every model on the platform, including gpt-image-2. No OpenAI organization verification required.
GPT Image 2 vs Nano Banana Pro — which is better?
Nano Banana Pro (Gemini 3 Pro Image) is cheaper per token, does native 4K, and grounds images in Search; gpt-image-2 leads on agentic layout planning and up to 16 reference images. Both run on one GPTProto key, so you can A/B them directly.
Does the GPT Image 2 API support image editing and references?
Yes. The editing endpoint takes mask images for precise inpaint / outpaint, and you can pass up to 16 reference images per call to hold subject and style consistency.
How do I improve gpt image 2 api lighting?
The gpt image 2 api has a significantly better understanding of lighting by default. To maximize this, use descriptive prompts regarding light sources. While some competitors handle flash instructions differently, the gpt api excels at reacting to environmental light within the generated scene automatically. By specifying 'soft morning light' or 'harsh neon', you guide the gpt image 2 engine to render realistic gpt shadows.
Is prompting different for gpt image 2 api?
Effective gpt image 2 api usage relies on specificity. Instead of broad terms, describe the scene in detail—such as a residential bathroom under construction. For cleaner results, especially in nature, use negative prompts to block speckling or grain patterns, ensuring the gpt image output remains sharp. The gpt image 2 api responds best to prompts around 20 words that focus on gpt material and gpt environmental details.
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