Overview
The OpenAI Platform API is the reference implementation most other providers copy. It exposes the GPT-4o, GPT-4o-mini, GPT-5-preview, o-series reasoning, and specialized models (Whisper, TTS, Embeddings, DALL-E). Its function calling with strict JSON schema is still the most reliable tool-use path in production, and the Assistants + Realtime APIs cover agents and voice with minimal glue code.
Capabilities
- Chat Completions with function calling and strict structured outputs.
- Assistants API with file search, code interpreter, and threaded state.
- Realtime API for low-latency voice agents.
- Batch API at 50% discount for async workloads.
- Fine-tuning across GPT-4o-mini and select variants.
Where it shines
- Structured Outputs (strict mode) eliminates 90%+ of malformed tool-call bugs.
- Latency and throughput are consistently near best-in-class.
- SDKs, docs, and community coverage are unmatched.
- Batch API halves the cost for anything that doesn't need to be synchronous.
Where it struggles
- Costs escalate fast on flagship models without careful routing.
- Rate limits on new orgs can trip production workloads — plan for tier upgrades.
- Content-policy filtering is stricter than most competitors; some legitimate workflows require an appeal.
Best for
- Any production feature where reliable tool calling matters more than raw cost.
- Voice agents (Realtime API is significantly ahead of alternatives).
- Teams that want one vendor across chat, embeddings, TTS, and vision.
Pricing notes
GPT-4o-mini ~$0.15/M input / $0.60/M output. GPT-4o ~$2.50/$10. o1 ~$15/$60. Batch API cuts these in half. Budget primarily on output tokens — that's where reasoning models get expensive.
Tutorials & patterns that work
Use Structured Outputs for every tool call
Set response_format to a JSON schema with strict:true. This forces the model to produce valid JSON matching your schema — no more parse-and-retry loops. Combine with tool_choice:'required' when a tool must fire.
Halve your bill with the Batch API
Anything non-interactive — nightly summarization, backfills, evals — belongs on Batch. Same models, 50% discount, 24-hour SLA. Move as much off the sync path as possible.
Route with a cheap-first pattern
Send every request to gpt-4o-mini first with a self-critique step. Only escalate to gpt-4o or o-series if the mini output flags low confidence. Typical savings: 60-80% at similar quality on aggregate.