{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"openrouter-openai-gpt-5-pro","slug":"openai-gpt-5-pro","name":"OpenAI: GPT-5 Pro","type":"model","url":"https://openrouter.ai/models/openai~gpt-5-pro","page_url":"https://unfragile.ai/openai-gpt-5-pro","categories":["model-training","testing-quality"],"tags":["openai","api-access","text","image"],"pricing":{"model":"paid","free":false,"starting_price":"$1.50e-5 per prompt token"},"status":"active","verified":false},"capabilities":[{"id":"openrouter-openai-gpt-5-pro__cap_0","uri":"capability://planning.reasoning.multi.step.reasoning.with.chain.of.thought.decomposition","name":"multi-step reasoning with chain-of-thought decomposition","description":"GPT-5 Pro implements advanced chain-of-thought reasoning that breaks complex problems into intermediate reasoning steps before generating final answers. The model uses transformer-based attention mechanisms to maintain coherence across multi-step logical chains, enabling it to handle problems requiring sequential inference, mathematical derivations, and multi-stage decision making. This approach improves accuracy on tasks where intermediate reasoning is critical by forcing explicit step-by-step problem decomposition rather than direct answer generation.","intents":["I need to solve complex math problems that require showing work and intermediate steps","I want to debug code by having the model reason through the logic step-by-step","I need to break down a complex business problem into logical sub-problems and solve each","I want the model to explain its reasoning process for transparency and verification"],"best_for":["researchers and engineers solving complex technical problems","educators building tutoring systems that require explanation","teams building AI agents that need interpretable decision-making"],"limitations":["Chain-of-thought reasoning increases token consumption by 2-5x compared to direct answers","Longer reasoning chains may accumulate errors in intermediate steps","Reasoning quality degrades on problems outside the training distribution"],"requires":["OpenAI API key with GPT-5 Pro access","HTTP client capable of streaming responses","Sufficient API quota for increased token usage"],"input_types":["natural language problem descriptions","mathematical expressions","code snippets with debugging context","multi-part logical puzzles"],"output_types":["step-by-step reasoning text","intermediate conclusions","final answer with justification"],"categories":["planning-reasoning","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-openai-gpt-5-pro__cap_1","uri":"capability://code.generation.editing.high.fidelity.code.generation.with.multi.language.support","name":"high-fidelity code generation with multi-language support","description":"GPT-5 Pro generates production-quality code across 40+ programming languages by leveraging transformer attention patterns trained on diverse code repositories and syntax trees. The model understands language-specific idioms, frameworks, and best practices, generating code that follows ecosystem conventions. It handles complex code generation tasks including multi-file projects, API integrations, and architectural patterns by maintaining semantic consistency across generated code blocks and understanding dependency relationships between modules.","intents":["I need to generate complete, working functions in Python, JavaScript, Go, Rust, etc.","I want to scaffold a new microservice with proper error handling and logging","I need to generate code that integrates with specific APIs and libraries correctly","I want to refactor existing code to follow best practices and design patterns"],"best_for":["full-stack developers accelerating feature development","teams building code generation tools and IDEs","developers learning new languages or frameworks"],"limitations":["Generated code may contain subtle logic errors requiring human review","Performance optimization and security hardening often require manual refinement","Context window limits prevent generating very large codebases (>50KB) in single requests","Code quality degrades for domain-specific languages and proprietary frameworks"],"requires":["OpenAI API key with GPT-5 Pro model access","Language-specific linters and test runners for validation","Version control system for tracking generated code changes"],"input_types":["natural language descriptions of desired functionality","existing code snippets for context and style matching","API documentation and schema definitions","architectural diagrams or pseudocode"],"output_types":["complete function implementations","multi-file project scaffolds","code refactoring suggestions","test cases and fixtures"],"categories":["code-generation-editing","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-openai-gpt-5-pro__cap_10","uri":"capability://text.generation.language.conversational.interaction.with.multi.turn.context.management","name":"conversational interaction with multi-turn context management","description":"GPT-5 Pro maintains coherent multi-turn conversations by tracking conversation history, understanding references and pronouns, and building on previous exchanges. The model manages context across turns, remembering facts established earlier in the conversation and maintaining consistency in responses. It understands conversational implicature, can clarify ambiguities, and adapts responses based on conversation flow and user preferences established through interaction.","intents":["I want to build a chatbot that maintains context across multiple conversation turns","I need the model to remember facts and preferences from earlier in the conversation","I want natural back-and-forth dialogue that builds on previous exchanges","I need the model to clarify ambiguities and ask follow-up questions when needed"],"best_for":["teams building conversational AI and chatbots","customer service automation","interactive tutoring and educational systems"],"limitations":["Context window limits prevent indefinitely long conversations","Model may forget information from very early in long conversations","Inconsistencies may emerge in very long conversations","Managing conversation state requires application-level logic"],"requires":["OpenAI API key with GPT-5 Pro access","Conversation history management in application","Message formatting following OpenAI chat format"],"input_types":["user messages in conversation","conversation history","system prompts defining assistant behavior"],"output_types":["assistant responses in conversation","clarifying questions","contextually appropriate replies"],"categories":["text-generation-language","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-openai-gpt-5-pro__cap_2","uri":"capability://text.generation.language.instruction.following.with.complex.constraint.satisfaction","name":"instruction-following with complex constraint satisfaction","description":"GPT-5 Pro implements improved instruction-following through enhanced semantic understanding of multi-part requirements, negations, and edge-case constraints. The model uses attention mechanisms to track and enforce multiple simultaneous constraints throughout generation, maintaining consistency with specified requirements even when they conflict or require careful prioritization. This enables handling of nuanced instructions like 'write in a professional tone but with humor, avoid mentioning X, ensure Y is emphasized, and keep it under 500 words.'","intents":["I need the model to follow a complex set of formatting and style requirements simultaneously","I want to specify what the output should NOT contain and have it respected","I need to enforce specific constraints like word count, structure, or tone across long outputs","I want to give detailed instructions with edge cases and have them all handled correctly"],"best_for":["content creators with specific brand voice and style guidelines","teams building content generation pipelines with strict requirements","researchers testing model instruction-following capabilities"],"limitations":["Constraint satisfaction degrades when requirements exceed 10-15 simultaneous constraints","Conflicting constraints may be resolved unpredictably without explicit prioritization","Negation constraints ('avoid X') are less reliable than positive constraints","Very specific formatting requirements may require multiple iterations to perfect"],"requires":["OpenAI API key with GPT-5 Pro access","Clear, well-structured prompt with explicit constraint ordering","Validation logic to verify constraint compliance in outputs"],"input_types":["natural language instructions with multiple constraints","structured prompt templates with variable substitution","examples of desired output format and style"],"output_types":["text content adhering to specified constraints","structured data matching format requirements","content with verified constraint compliance"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-openai-gpt-5-pro__cap_3","uri":"capability://image.visual.vision.based.image.understanding.and.analysis","name":"vision-based image understanding and analysis","description":"GPT-5 Pro processes images through a vision transformer architecture that extracts semantic features from visual content, enabling detailed image analysis, object detection, scene understanding, and text extraction from images. The model integrates vision and language understanding to answer questions about images, describe visual content in natural language, and identify relationships between visual elements. It handles multiple image formats and can process images at various resolutions while maintaining semantic understanding.","intents":["I need to extract text from screenshots, documents, or photos (OCR functionality)","I want to analyze an image and answer specific questions about its content","I need to describe what's happening in an image in natural language","I want to identify objects, people, or patterns in images for classification tasks"],"best_for":["developers building document processing and OCR applications","teams creating visual search and image analysis tools","content moderation and accessibility teams"],"limitations":["Image resolution limits may affect accuracy for small text or fine details","Cannot generate or edit images, only analyze existing images","Performance on specialized domains (medical imaging, satellite imagery) may be limited","Bias in training data may affect object recognition and scene understanding"],"requires":["OpenAI API key with GPT-5 Pro vision capability enabled","Images in supported formats (JPEG, PNG, WebP, GIF)","Base64 encoding or URL access for image transmission"],"input_types":["JPEG, PNG, WebP, GIF images","screenshots and document scans","photographs and diagrams","natural language questions about image content"],"output_types":["natural language descriptions of image content","extracted text from images","answers to questions about images","structured data about detected objects and relationships"],"categories":["image-visual","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-openai-gpt-5-pro__cap_4","uri":"capability://tool.use.integration.api.integration.and.function.calling.with.schema.based.dispatch","name":"api integration and function calling with schema-based dispatch","description":"GPT-5 Pro supports structured function calling through a schema-based interface that allows the model to invoke external APIs and tools by generating structured JSON payloads matching predefined function signatures. The model understands when to call functions, generates properly formatted arguments, and can chain multiple function calls to accomplish complex tasks. This enables integration with external services, databases, and custom business logic while maintaining semantic understanding of function purposes and argument requirements.","intents":["I want the model to call my API endpoints to fetch real-time data or perform actions","I need to build an AI agent that can use multiple tools to accomplish complex tasks","I want to integrate the model with my database or business logic layer","I need the model to make decisions about which functions to call based on user requests"],"best_for":["teams building AI agents and autonomous systems","developers creating chatbots with external tool integration","enterprises integrating LLMs with existing business systems"],"limitations":["Function calling adds latency due to round-trip API calls and model inference cycles","Model may hallucinate function calls or generate invalid schemas requiring validation","Complex function chaining may require explicit orchestration and error handling","Limited to functions that can be described in schema format"],"requires":["OpenAI API key with function calling capability","JSON schema definitions for all callable functions","Backend implementation of function handlers","Error handling and validation logic for function responses"],"input_types":["natural language requests requiring function invocation","function schema definitions in JSON format","function execution results and responses"],"output_types":["structured function call requests (JSON)","function execution results","natural language responses incorporating function data"],"categories":["tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-openai-gpt-5-pro__cap_5","uri":"capability://memory.knowledge.long.context.understanding.with.128k.token.window","name":"long-context understanding with 128k token window","description":"GPT-5 Pro maintains a 128,000 token context window that enables processing of very long documents, code repositories, and conversation histories without losing semantic coherence. The model uses efficient attention mechanisms and positional encoding schemes to handle long sequences while maintaining performance on tasks requiring reference to distant context. This allows processing entire books, large codebases, or extended conversations in single requests while maintaining understanding of relationships between distant parts of the context.","intents":["I need to analyze an entire codebase or multiple files together for refactoring","I want to process a full research paper or book and extract insights","I need to maintain conversation context over very long multi-turn interactions","I want to analyze large datasets or logs for patterns and anomalies"],"best_for":["developers working with large codebases and complex projects","researchers analyzing long documents and papers","teams building conversational AI with extended memory requirements"],"limitations":["Token consumption scales linearly with context length, increasing API costs significantly","Performance may degrade on tasks requiring precise recall of information from middle of context","Context window is still insufficient for processing entire large-scale datasets","Longer contexts increase latency for model inference"],"requires":["OpenAI API key with GPT-5 Pro access","Sufficient API quota for high token consumption","Text tokenization to fit content within 128K token limit"],"input_types":["long-form text documents","multiple code files and repositories","extended conversation histories","large structured data and logs"],"output_types":["analysis and insights from long documents","refactoring suggestions for large codebases","summaries maintaining context from entire input","answers referencing distant parts of context"],"categories":["memory-knowledge","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-openai-gpt-5-pro__cap_6","uri":"capability://data.processing.analysis.structured.data.extraction.and.schema.based.output.generation","name":"structured data extraction and schema-based output generation","description":"GPT-5 Pro can generate structured outputs matching predefined JSON schemas, enabling reliable extraction of information into structured formats and generation of data that conforms to specific requirements. The model understands schema constraints and generates valid JSON that matches type definitions, required fields, and nested structures. This capability enables integration with downstream systems that require structured data, database insertion, and programmatic processing of model outputs.","intents":["I need to extract structured data from unstructured text (names, dates, amounts, etc.)","I want to generate JSON responses that match my API schema exactly","I need to convert natural language descriptions into structured database records","I want to ensure model outputs are always valid and parseable by my application"],"best_for":["teams building data extraction and ETL pipelines","developers creating APIs that need structured LLM outputs","enterprises processing documents and forms at scale"],"limitations":["Complex nested schemas may confuse the model or result in invalid JSON","Schema validation requires additional parsing and error handling","Model may omit optional fields or generate null values unexpectedly","Very large schemas (100+ fields) may exceed model's ability to follow constraints"],"requires":["OpenAI API key with structured output capability","JSON schema definitions for expected output format","JSON validation and parsing logic in application"],"input_types":["unstructured text to extract data from","natural language descriptions of desired data","JSON schema definitions"],"output_types":["valid JSON matching schema","structured data records","typed data objects"],"categories":["data-processing-analysis","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-openai-gpt-5-pro__cap_7","uri":"capability://text.generation.language.content.generation.with.style.and.tone.control","name":"content generation with style and tone control","description":"GPT-5 Pro generates diverse content types (articles, emails, social media posts, creative writing) with fine-grained control over style, tone, and voice. The model understands stylistic dimensions like formality, humor, technical depth, and emotional tone, applying them consistently throughout generated content. This enables creating content that matches brand voice, audience expectations, and specific use cases while maintaining coherence and quality across longer pieces.","intents":["I need to generate marketing copy that matches my brand voice and tone","I want to create multiple versions of content with different tones for A/B testing","I need to generate professional emails, reports, or documentation","I want to create creative content (stories, poetry, scripts) with specific stylistic elements"],"best_for":["marketing and content teams automating content creation","copywriters and creative professionals accelerating workflows","companies generating personalized customer communications"],"limitations":["Tone consistency may degrade in very long pieces (>5000 words)","Subtle stylistic nuances may require manual refinement","Generated content may lack originality or contain clichés","Humor and sarcasm may not translate well across all audiences"],"requires":["OpenAI API key with GPT-5 Pro access","Clear style and tone guidelines or examples","Human review process for quality assurance"],"input_types":["content briefs and outlines","style and tone specifications","examples of desired voice and style","target audience descriptions"],"output_types":["marketing copy and advertisements","articles and blog posts","emails and communications","creative writing and stories"],"categories":["text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-openai-gpt-5-pro__cap_8","uri":"capability://text.generation.language.multilingual.understanding.and.translation.with.context.preservation","name":"multilingual understanding and translation with context preservation","description":"GPT-5 Pro understands and processes 100+ languages with improved semantic understanding of language-specific idioms, cultural context, and nuance. The model can translate between languages while preserving meaning, tone, and cultural context, and can understand code-mixed text and transliteration. It maintains semantic coherence across language boundaries and understands when direct translation is inappropriate, instead conveying meaning through culturally appropriate alternatives.","intents":["I need to translate content between languages while preserving tone and meaning","I want to understand and respond to user input in multiple languages","I need to process multilingual documents and extract information across languages","I want to generate content in specific languages with cultural appropriateness"],"best_for":["global companies serving multilingual user bases","translation and localization teams","developers building international applications"],"limitations":["Translation quality varies significantly by language pair and domain","Rare languages and dialects may have limited training data","Cultural context and idioms may not translate perfectly","Code-mixed text and transliteration may confuse the model"],"requires":["OpenAI API key with GPT-5 Pro access","Source and target language specifications","Context about cultural appropriateness when relevant"],"input_types":["text in any supported language","multilingual documents","code-mixed text","transliterated text"],"output_types":["translated text in target language","multilingual responses","language-specific content generation"],"categories":["text-generation-language","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-openai-gpt-5-pro__cap_9","uri":"capability://planning.reasoning.mathematical.reasoning.and.symbolic.computation","name":"mathematical reasoning and symbolic computation","description":"GPT-5 Pro demonstrates improved mathematical reasoning capabilities, handling algebra, calculus, statistics, and symbolic computation with step-by-step derivations. The model understands mathematical notation, can verify proofs, and explains mathematical concepts. It integrates symbolic reasoning with natural language explanation, making mathematics accessible while maintaining rigor. The model can work with equations, formulas, and mathematical structures while explaining the reasoning behind each step.","intents":["I need to solve complex math problems with step-by-step explanations","I want to verify mathematical proofs or check derivations","I need to explain mathematical concepts to students","I want to work with equations and symbolic expressions"],"best_for":["educators and tutoring platforms","students learning mathematics","researchers and engineers solving mathematical problems","teams building educational AI applications"],"limitations":["Very complex proofs may exceed the model's reasoning capacity","Numerical computation is approximate, not exact","Symbolic manipulation is limited compared to dedicated math software","Performance degrades on problems requiring extensive calculation"],"requires":["OpenAI API key with GPT-5 Pro access","Mathematical notation understanding (LaTeX, ASCII math)","Validation against known solutions or symbolic math tools"],"input_types":["mathematical problems in natural language","equations and formulas","mathematical proofs","symbolic expressions"],"output_types":["step-by-step solutions","mathematical explanations","verified proofs","symbolic derivations"],"categories":["planning-reasoning","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":26,"verified":false,"data_access_risk":"high","permissions":["OpenAI API key with GPT-5 Pro access","HTTP client capable of streaming responses","Sufficient API quota for increased token usage","OpenAI API key with GPT-5 Pro model access","Language-specific linters and test runners for validation","Version control system for tracking generated code changes","Conversation history management in application","Message formatting following OpenAI chat format","Clear, well-structured prompt with explicit constraint ordering","Validation logic to verify constraint compliance in outputs"],"failure_modes":["Chain-of-thought reasoning increases token consumption by 2-5x compared to direct answers","Longer reasoning chains may accumulate errors in intermediate steps","Reasoning quality degrades on problems outside the training distribution","Generated code may contain subtle logic errors requiring human review","Performance optimization and security hardening often require manual refinement","Context window limits prevent generating very large codebases (>50KB) in single requests","Code quality degrades for domain-specific languages and proprietary frameworks","Context window limits prevent indefinitely long conversations","Model may forget information from very early in long conversations","Inconsistencies may emerge in very long conversations","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.47,"ecosystem":0.37,"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-pro","compare_url":"https://unfragile.ai/compare?artifact=openai-gpt-5-pro"}},"signature":"+1TRekXyO9e4caF0IBwBgvIEZUQHQRIbvMgpZB/OwTGOUQXOlwu25sJq7rfNXS4KibVWyPFM9zzXkzvoS6fWAA==","signedAt":"2026-06-19T11:12:29.346Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/openai-gpt-5-pro","artifact":"https://unfragile.ai/openai-gpt-5-pro","verify":"https://unfragile.ai/api/v1/verify?slug=openai-gpt-5-pro","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"}}