GPT-4o
GPT-4o is OpenAI's first natively multimodal "omni" model, unifying text, audio, image, and video processing within a single end-to-end trained architecture and delivering audio response times averaging 320 milliseconds, comparable to human conversational latency.
import { streamText } from 'ai'
const result = streamText({ model: 'openai/gpt-4o', prompt: 'Why is the sky blue?'})What To Consider When Choosing a Provider
Zero Data Retention
AI Gateway supports Zero Data Retention for this model via direct gateway requests (BYOK is not included). To configure this, check the documentation.Authentication
AI Gateway authenticates requests using an API key or OIDC token. You do not need to manage provider credentials directly.
For applications that mix modalities (for example, a voice interface that also accepts image uploads), a single model endpoint simplifies both architecture and cost accounting compared to separate specialist models.
When to Use GPT-4o
Best For
Real-time voice applications:
Native audio processing eliminates pipeline latency between speech recognition, reasoning, and synthesis
Mixed-modality workflows:
Processing both images and text together for visual question answering or document analysis with figures
Cost-efficient GPT-4 quality:
Applications that need GPT-4-class text quality with lower API cost than GPT-4 Turbo
Multilingual applications:
Products that benefit from GPT-4o's improved non-English text performance
Evolving multimodal products:
Apps that may expand from text-only to multimodal inputs over time with a single model supporting that evolution
Consider Alternatives When
Maximum coding capability:
GPT-4.1 benchmarks are meaningfully better for some coding use cases
Cost-driven workloads:
GPT-4.1 mini provides sufficient quality at lower cost
Deep multi-step reasoning:
The o-series reasoning models' chain-of-thought approach is superior for complex analytical problems
Conclusion
GPT-4o introduced native omni-modal processing as a practical API capability, eliminating the latency penalties of chained pipeline architectures and matching GPT-4 Turbo quality at lower cost. For applications that need a single model to handle text, audio, and vision inputs reliably, it remains a strong foundation through AI Gateway.
FAQ
It reflects the model's end-to-end native training across text, audio, image, and video modalities, rather than being a combination of separate specialist models connected by a pipeline.
GPT-4o averages 320 milliseconds for audio responses; the prior GPT-4 Turbo-based voice approach averaged 5.4 seconds, making GPT-4o approximately 16x faster for voice.
GPT-4o launched at lower API cost than GPT-4 Turbo while matching its performance on English text and code, and improving on non-English languages.
Inputs: text, audio, image, video. Outputs: text, audio, and image. This breadth makes it flexible for diverse multimodal application architectures.
No. The alias gpt-4o points to the latest stable version, which may be updated over time. Dated snapshots like gpt-4o-2024-05-13 or gpt-4o-2024-11-20 pin to specific releases.
AI Gateway is designed as a lightweight routing layer. For most applications, the observability, caching, and authentication benefits outweigh any marginal overhead.
This page shows live throughput and time-to-first-token metrics measured across real AI Gateway traffic.
