OpenAI • audio
OpenAI speech-to-text model optimized for more accurate transcription than older Whisper-based production defaults.
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GPT-4o Transcribe results on the main AI model evaluation benchmarks. Higher scores indicate better performance.
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| SWEN Audio API Readiness | 96.0 | 100.0 | SWEN Audio Registry v2026-06-22. Editorial multimodal ranking with modality-specific scoring based on product capability, control, speed, value and integration readiness. |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| SWEN Audio Composite | 91.4 | 100.0 | SWEN Audio Registry v2026-06-22. Editorial multimodal ranking with modality-specific scoring based on product capability, control, speed, value and integration readiness. |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| SWEN Audio Control | 82.0 | 100.0 | SWEN Audio Registry v2026-06-22. Editorial multimodal ranking with modality-specific scoring based on product capability, control, speed, value and integration readiness. |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| SWEN Audio Latency | 84.0 | 100.0 | SWEN Audio Registry v2026-06-22. Editorial multimodal ranking with modality-specific scoring based on product capability, control, speed, value and integration readiness. |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| SWEN Audio Quality | 95.0 | 100.0 | SWEN Audio Registry v2026-06-22. Editorial multimodal ranking with modality-specific scoring based on product capability, control, speed, value and integration readiness. |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| SWEN Audio Value | 88.0 | 100.0 | SWEN Audio Registry v2026-06-22. Editorial multimodal ranking with modality-specific scoring based on product capability, control, speed, value and integration readiness. |
GPT-4o Transcribe is an AI model developed by OpenAI, classified as a audio model. It is a multimodal model, capable of processing text, images, and potentially other media types. As a proprietary model, it is available via OpenAI's cloud API.
GPT-4o Transcribe does not have public per-token pricing available at this time. Some models offer access via enterprise plans or research programs. Check OpenAI's official website for up-to-date availability and pricing.
GPT-4o Transcribe was evaluated on 6 different benchmarks, covering categories like API Readiness, audio, Control, Latency, Quality, Value. Results show exceptional performance across available evaluations.
It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.
GPT-4o Transcribe specializes in audio, offering advanced capabilities for creating and processing audio content.
In the 2026 AI model ecosystem, GPT-4o Transcribe competes directly with similarly capable models. Key competitors include Claude (Anthropic), Gemini (Google), and open source models like Llama (Meta) and Qwen (Alibaba). The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.
For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.
OpenAI speech-to-text model optimized for more accurate transcription than older Whisper-based production defaults.
GPT-4o Transcribe does not have public per-token pricing available at this time. Check OpenAI's official website for up-to-date information.
In available benchmarks, GPT-4o Transcribe scored: SWEN Audio API Readiness: 96/100, SWEN Audio Composite: 91.4/100, SWEN Audio Control: 82/100. See the full table above for a detailed comparison.
No, GPT-4o Transcribe is a proprietary model from OpenAI. It is available via cloud API. For open source alternatives, check our open source model ranking.
GPT-4o Transcribe excels at general-purpose language tasks.
Last updated: June 22, 2026 • View methodology →