gpt-image-2listed

# GPT Image 2 (ChatGPT Images 2.0) OpenAI's latest image model — the strongest model available for **legible text inside images**. Use this when the picture *is* the typography: chalkboards, store signs, hand-lettered posters, menu boards, magazine covers, packaging mockups, UI screenshots, book covers. **Two endpoints:** - **Text-to-image** (`openai/gpt-image-2`) — generate from a prompt - **Image edit** (`openai/gpt-image-2/edit`) — modify a reference image (with optional mask for region-specific edits) | Field | Value | |-------|-------| | Model ID | `openai/gpt-image-2` (text-to-image) · `openai/gpt-image-2/edit` (edit) | | Provider | Fal AI | | Method | Sync (POST → response with image URLs, no polling) | | Type | Image generation + editing | | API Key | `.env` → `FAL_KEY` | | Docs | https://fal.ai/models/openai/gpt-image-2 · https://fal.ai/models/openai/gpt-image-2/edit | --- ## Setup 1. Get a Fal API key from https://fal.ai/dashboard/keys 2. Add to your `.env` file (or wherever your project keeps secrets): ``` FAL_KEY=your_key_here ``` 3. That's it. Sync API — no SDK install required, just `curl` or `fetch`. --- ## How to call it Auth header is `Authorization: Key {key}` — **not** `Bearer`. This applies to both endpoints. ### Text-to-image — minimum request ```bash curl -s -X POST "https://fal.run/openai/gpt-image-2" \ -H "Authorization: Key $FAL_KEY" \ -H "Content-Type: application/json" \ -d '{"prompt": "A vintage diner chalkboard reading TO