GPT-4o ("omni") is OpenAI's flagship multimodal model that processes text, images, and audio natively in a unified architecture. Key specs: 128k context window, $2.50/M input tokens, $10/M output tokens (Dec 2024). GPT-4o excels at coding, reasoning, and structured outputs with function calling. GPT-4o-mini ($0.15/M input) handles 85%+ of tasks at 10% cost. The o1/o3 series adds extended reasoning via chain-of-thought for math and science problems.
Each stage in order — click any step to read what it does.
OpenAI model tiers and use cases.
The trade-offs worth knowing before you build this.
Instead of prompting 'respond in JSON format' (unreliable), use response_format with json_schema. GPT-4o guarantees valid JSON matching your Zod/Pydantic schema — eliminating parse errors in production.
GPT-4o-mini handles summarisation, classification, extraction, and light reasoning at 85%+ quality for 1/16th the price. A/B test your prompts on both models and upgrade only when quality gap affects user outcomes.
o1/o3 models cost 5-10x more and respond slower. They shine on competition math, science, and complex coding. For most product features (chat, search, summarisation), GPT-4o produces equivalent quality faster and cheaper.
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