{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"openrouter-openai-gpt-5-image-mini","slug":"openai-gpt-5-image-mini","name":"OpenAI: GPT-5 Image Mini","type":"model","url":"https://openrouter.ai/models/openai~gpt-5-image-mini","page_url":"https://unfragile.ai/openai-gpt-5-image-mini","categories":["image-generation"],"tags":["openai","api-access","text","image"],"pricing":{"model":"paid","free":false,"starting_price":"$2.50e-6 per prompt token"},"status":"active","verified":false},"capabilities":[{"id":"openrouter-openai-gpt-5-image-mini__cap_0","uri":"capability://image.visual.multimodal.text.to.image.generation.with.instruction.following","name":"multimodal text-to-image generation with instruction following","description":"Generates images from natural language prompts using GPT-5 Mini's advanced language understanding combined with GPT Image 1 Mini's generation backbone. The model processes textual instructions through a unified transformer architecture that maintains semantic coherence between language comprehension and visual synthesis, enabling precise control over composition, style, and content through detailed prompts without separate prompt engineering.","intents":["Generate product mockups and marketing visuals from detailed text descriptions","Create concept art and design variations by iterating on prompt instructions","Produce illustrations and visual content for content creators without design skills","Generate training data or synthetic images for computer vision applications"],"best_for":["Product teams needing rapid visual prototyping without design resources","Content creators and marketers generating bulk visual assets","Developers building image generation into applications via API","Teams requiring high instruction-following fidelity in generated outputs"],"limitations":["Generation latency typically 5-30 seconds per image depending on complexity and queue load","Output resolution and aspect ratio constraints inherited from GPT Image 1 Mini architecture","No fine-tuning or style transfer capabilities — limited to prompt-based control","Rate limiting applies per API key; batch generation requires request queuing","Cannot generate images of real identifiable people or copyrighted characters with high fidelity"],"requires":["OpenAI API key with image generation quota enabled","HTTP/REST client or OpenAI SDK (Python 3.8+, Node.js 14+, etc.)","Network connectivity to OpenAI endpoints via OpenRouter proxy","Sufficient API credits for image generation (pricing per image, not per token)"],"input_types":["natural language text prompts (English optimized, supports other languages with degradation)","structured prompt templates with variable substitution"],"output_types":["PNG images (default format)","JPEG images (via format parameter)","Base64-encoded image data (for direct embedding)","HTTPS URLs to generated images (with expiration)"],"categories":["image-visual","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-openai-gpt-5-image-mini__cap_1","uri":"capability://image.visual.native.multimodal.context.understanding.with.image.inputs","name":"native multimodal context understanding with image inputs","description":"Accepts both text and image inputs in a single request, processing them through a unified embedding space where visual and textual information are jointly understood. The model uses cross-modal attention mechanisms to correlate image content with text instructions, enabling tasks like image captioning, visual question answering, and image-guided generation without separate preprocessing or vision encoders.","intents":["Analyze uploaded images and generate descriptions or metadata","Answer questions about image content or visual relationships","Use reference images to guide or constrain image generation","Extract text or structured data from images (OCR-like functionality)"],"best_for":["Developers building multimodal AI applications that need unified input handling","Teams processing mixed text-image workflows without pipeline orchestration","Applications requiring visual context to inform text generation or image synthesis"],"limitations":["Image input size limited to ~20MB per request; very high-resolution images may be downsampled","No video input support — only static images","Cross-modal understanding quality degrades for abstract or highly stylized images","Batch processing of multiple images requires sequential API calls (no native batching)"],"requires":["OpenAI API key with vision capabilities enabled","Images in supported formats: JPEG, PNG, GIF, WebP","Base64 encoding or HTTPS URL for image transmission","Sufficient API credits for multimodal requests (higher token cost than text-only)"],"input_types":["text prompts (required)","image files (JPEG, PNG, GIF, WebP)","base64-encoded image data","HTTPS URLs pointing to publicly accessible images"],"output_types":["text responses (descriptions, answers, analysis)","generated images (when generation is requested)","structured JSON (if prompted for extraction)"],"categories":["image-visual","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-openai-gpt-5-image-mini__cap_2","uri":"capability://image.visual.batch.image.generation.with.deterministic.seeding","name":"batch image generation with deterministic seeding","description":"Supports reproducible image generation through seed parameters, allowing developers to generate multiple variations of the same prompt or recreate specific outputs for testing and validation. The implementation uses deterministic random number generation seeded at the diffusion model level, ensuring bit-identical outputs across multiple API calls when seed and all parameters remain constant.","intents":["Generate consistent visual variations for A/B testing or comparison","Reproduce specific generated images for debugging or quality assurance","Create deterministic test suites for image generation pipelines","Generate multiple style variations of the same concept with controlled randomness"],"best_for":["QA and testing teams validating image generation quality","Researchers conducting reproducible experiments with generative models","Developers building deterministic workflows that require image consistency"],"limitations":["Seed parameter only guarantees reproducibility within the same model version; model updates may break determinism","Seeding adds minimal latency but requires explicit parameter passing per request","No seed-based interpolation or morphing between two seed outputs","Determinism applies only to the diffusion process; prompt interpretation may vary slightly across API versions"],"requires":["OpenAI API key with image generation enabled","Knowledge of seed parameter syntax and valid seed ranges (typically 0-2^32-1)","Ability to track and version seed values in application logic"],"input_types":["text prompts","integer seed values (0 to 4294967295)"],"output_types":["PNG or JPEG images (deterministically generated)","image metadata including seed value used"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-openai-gpt-5-image-mini__cap_3","uri":"capability://image.visual.api.based.image.generation.with.streaming.and.async.patterns","name":"api-based image generation with streaming and async patterns","description":"Exposes image generation through REST and gRPC APIs with support for asynchronous request handling, polling-based status checks, and webhook callbacks. The implementation uses OpenRouter's proxy layer to abstract OpenAI's underlying API, providing standardized request/response schemas, automatic retry logic with exponential backoff, and request queuing to handle burst traffic without overwhelming the backend.","intents":["Integrate image generation into web applications or mobile apps via HTTP requests","Build serverless functions that trigger image generation and store results","Implement long-polling or webhook-based workflows for asynchronous generation","Batch generate multiple images with automatic retry and error handling"],"best_for":["Full-stack developers building image generation features into web/mobile applications","Backend engineers implementing asynchronous job queues for image synthesis","Teams using OpenRouter for multi-model abstraction and cost optimization","Startups needing standardized API contracts across multiple image generation providers"],"limitations":["API latency adds 100-500ms overhead on top of generation time due to OpenRouter proxy layer","Webhook delivery is not guaranteed; applications must implement idempotency and retry logic","No native streaming of image generation progress; only completion-based callbacks","Rate limiting enforced at both OpenRouter and OpenAI levels; burst requests may queue","Image URLs expire after 24 hours; applications must download and store images if persistence is needed"],"requires":["OpenAI API key configured in OpenRouter account","HTTP client library (curl, axios, requests, fetch, etc.)","Understanding of async/await patterns or callback-based concurrency","Webhook endpoint with HTTPS and proper signature verification (if using callbacks)"],"input_types":["JSON request bodies with prompt, size, quality, and seed parameters","multipart/form-data for image uploads (if using image-guided generation)"],"output_types":["JSON responses with image URLs and metadata","HTTP 202 Accepted for async requests with polling endpoint","Webhook POST requests with generated image data"],"categories":["image-visual","tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-openai-gpt-5-image-mini__cap_4","uri":"capability://text.generation.language.advanced.prompt.interpretation.with.semantic.understanding","name":"advanced prompt interpretation with semantic understanding","description":"Leverages GPT-5 Mini's language understanding to parse complex, nuanced, and ambiguous prompts, extracting intent, style preferences, composition constraints, and implicit requirements before passing them to the image synthesis engine. The model uses chain-of-thought reasoning internally to decompose multi-part prompts into visual generation parameters, handling negations, conditional logic, and style references that simpler prompt parsers would miss.","intents":["Generate images from complex, multi-constraint prompts without manual prompt engineering","Specify conditional visual elements (e.g., 'if sunny, add shadows; if rainy, add puddles')","Reference artistic styles, historical periods, or cultural aesthetics using natural language","Combine multiple conflicting visual preferences and have the model resolve them intelligently"],"best_for":["Creative professionals and designers who think in natural language rather than prompt syntax","Non-technical users generating images without prompt engineering knowledge","Applications requiring flexible, conversational image generation interfaces"],"limitations":["Semantic understanding adds 1-3 seconds of latency for prompt interpretation before generation begins","Ambiguous or contradictory prompts may be resolved in unexpected ways; no explicit conflict resolution UI","Understanding quality degrades for very short prompts (< 10 words) or highly technical/domain-specific language","No explicit control over how the model prioritizes conflicting constraints"],"requires":["OpenAI API key with GPT-5 Mini access","Natural language prompts (English preferred; other languages supported with degradation)","Acceptance of non-deterministic interpretation for ambiguous inputs"],"input_types":["natural language text prompts (conversational, descriptive, or constraint-based)","prompts with negations ('without', 'no', 'avoid')","prompts with conditional logic ('if', 'when', 'depending on')"],"output_types":["generated images reflecting interpreted intent","implicit visual parameters (style, composition, mood) derived from prompt"],"categories":["text-generation-language","image-visual","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-openai-gpt-5-image-mini__cap_5","uri":"capability://image.visual.image.quality.and.style.control.with.parameter.tuning","name":"image quality and style control with parameter tuning","description":"Exposes fine-grained control over image generation quality, resolution, aspect ratio, and stylistic properties through API parameters. The implementation maps user-facing quality settings (e.g., 'standard', 'hd') to underlying diffusion model configurations, allowing developers to trade off generation speed, visual fidelity, and API cost without changing prompts or requiring model fine-tuning.","intents":["Generate high-quality images for print or professional use","Create fast, lower-quality previews for rapid iteration","Control output aspect ratios for specific use cases (social media, print, web)","Optimize API costs by adjusting quality settings based on use case requirements"],"best_for":["Product teams balancing quality, speed, and cost in image generation workflows","Developers building user-facing image generation with quality selection","Content creators needing different quality tiers for different distribution channels"],"limitations":["Higher quality settings (HD) incur 2-4x API cost and 2-3x longer generation time","Aspect ratio support is limited to predefined options (e.g., 1:1, 16:9, 9:16); custom ratios not supported","Quality improvements are model-dependent; 'HD' mode may not be available for all image sizes","No per-region quality control; entire image uses the same quality setting"],"requires":["OpenAI API key with image generation enabled","Knowledge of supported quality levels and aspect ratios","API parameter documentation for quality and size specifications"],"input_types":["quality parameter ('standard' or 'hd')","size parameter (e.g., '1024x1024', '1792x1024')","aspect ratio specification"],"output_types":["PNG or JPEG images at specified quality and resolution","metadata including actual resolution and quality mode used"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":23,"verified":false,"data_access_risk":"low","permissions":["OpenAI API key with image generation quota enabled","HTTP/REST client or OpenAI SDK (Python 3.8+, Node.js 14+, etc.)","Network connectivity to OpenAI endpoints via OpenRouter proxy","Sufficient API credits for image generation (pricing per image, not per token)","OpenAI API key with vision capabilities enabled","Images in supported formats: JPEG, PNG, GIF, WebP","Base64 encoding or HTTPS URL for image transmission","Sufficient API credits for multimodal requests (higher token cost than text-only)","OpenAI API key with image generation enabled","Knowledge of seed parameter syntax and valid seed ranges (typically 0-2^32-1)"],"failure_modes":["Generation latency typically 5-30 seconds per image depending on complexity and queue load","Output resolution and aspect ratio constraints inherited from GPT Image 1 Mini architecture","No fine-tuning or style transfer capabilities — limited to prompt-based control","Rate limiting applies per API key; batch generation requires request queuing","Cannot generate images of real identifiable people or copyrighted characters with high fidelity","Image input size limited to ~20MB per request; very high-resolution images may be downsampled","No video input support — only static images","Cross-modal understanding quality degrades for abstract or highly stylized images","Batch processing of multiple images requires sequential API calls (no native batching)","Seed parameter only guarantees reproducibility within the same model version; model updates may break determinism","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.37,"ecosystem":0.27,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.35,"quality":0.2,"ecosystem":0.1,"match_graph":0.3,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:24.485Z","last_scraped_at":"2026-05-03T15:20:45.776Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=openai-gpt-5-image-mini","compare_url":"https://unfragile.ai/compare?artifact=openai-gpt-5-image-mini"}},"signature":"hUwP/08BbdHj8xwEMaPa7zHbhDSqtBsv0MEXpK3ZT1J6aA2K94wRvxOs50GPt1nREBUQLAfN2sqUhfME4R6EBg==","signedAt":"2026-06-20T09:29:18.615Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/openai-gpt-5-image-mini","artifact":"https://unfragile.ai/openai-gpt-5-image-mini","verify":"https://unfragile.ai/api/v1/verify?slug=openai-gpt-5-image-mini","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}