Input: $1.57, Output: $12.5

Cost per million tokens

For enterprise pricing and custom weights or models

GPT-5 – Advanced AI Agent Model

What is GPT-5?

GPT-5 represents a leap toward artificial general intelligence (AGI) by functioning as an AI agent that “thinks” and builds with integrated tools. Beyond text completion, GPT-5 orchestrates web searches, code interpreters, and side-effect actions in parallel, following structured guidance to solve complex engineering tasks. While its creative writing lags slightly behind GPT-4.5, it excels at automating workflows, generating production-ready code, and navigating multi-step problem-solving environments.

Key Features

  • Agent-Based Reasoning: Chains tool calls (web search, code execution, data retrieval) to accomplish end-to-end tasks without manual orchestration.
  • Parallel Tool Usage: Simultaneously invokes multiple plugins or interpreters, reducing round trips and increasing throughput on complex tasks.
  • Structured Guidance Compliance: Adheres to developer-provided schemas, style guides, and validation rules to produce reliable, consistent outputs.
  • Software Engineering Mastery: Excels at debugging, code generation, refactoring, and writing test suites across popular languages (Python, JavaScript, Go).
  • Production-Ready Output: Generates deployable microservices, CI/CD scripts, and infrastructure-as-code templates with minimal post-processing.

Best Use Cases

  • Automated Coding Assistants: Scaffold APIs, write unit tests, and optimize algorithms in real time.
  • Intelligent Documentation: Auto-generate SDK docs, release notes, and interactive tutorials synchronized with code changes.
  • Data Analysis Workflows: Ingest datasets, run statistical models or SQL queries via the code interpreter tool, and visualize results programmatically.
  • DevOps Automation: Create deployment pipelines, configure containers, and manage cloud resources through scripted agent actions.
  • Research & Prototyping: Rapidly iterate on prototypes by querying external data sources and synthesizing findings.

Prompt Tips and Output Quality

  1. Be Specific: Clearly define objectives and expected formats. E.g., “Generate a Flask API that…”
  2. Leverage Tools: Mention required tools by name (web_search, code_interpreter) in your prompt to trigger agent capabilities.
  3. Structured Prompts: Use bullet lists, JSON schemas, or function definitions to guide GPT-5’s output format.
  4. Optional Image Inputs: Attach high-resolution diagrams or screenshots via the image parameter to enrich context for technical explanations.
  5. Iterate & Validate: Review generated code or actions, then instruct GPT-5 to refactor or optimize based on test results.

FAQs

Q: What is GPT-5 used for?
A: Automating end-to-end software tasks—from code generation and testing to deployment—while integrating web search and data tools.

Q: How does GPT-5 differ from GPT-4.5?
A: GPT-5 prioritizes agent-based workflows and parallel tool usage, delivering production-ready code more efficiently; creative writing is slightly less polished.

Q: Can GPT-5 generate production-ready applications?
A: Yes. It scaffolds code, writes tests, configures CI/CD, and follows your structured guidance to produce deployable artifacts.

Q: Does GPT-5 support creative writing?
A: It can draft narratives, but its strength lies in technical, agent-driven problem solving rather than imaginative prose.

Q: What input formats does GPT-5 accept?
A:

  • prompt (string, required): text commands or questions.
  • image (file, optional): diagrams or screenshots to add visual context.