gpt-realtime – OpenAI’s newly released speech model

What is gpt-realtime？

gpt-realtime is OpenAI’s latest advanced speech model, designed for real-world tasks. The model can generate high-quality, natural speech, supporting multiple languages and voice styles. It can understand non-verbal cues and adjust tone based on context. Through the Realtime API, it also supports image input, enabling conversations based on visual content. gpt-realtime shows significant improvements in instruction-following and function calling, making it suitable for customer service, education, finance, healthcare, and other scenarios, providing smarter and more flexible voice interactions.

Main Features of gpt-realtime

High-Quality Speech Generation: gpt-realtime produces natural, high-quality speech in multiple languages and styles, such as “speak quickly and professionally” or “speak empathetically with a French accent.”
Speech Understanding and Interaction: The model can understand raw audio, accurately capture non-verbal cues (e.g., laughter), switch languages mid-sentence, and adjust tone according to context.
Instruction-Following Ability: The model excels at following instructions, with instruction-following accuracy rising from 20.6% in previous models to 30.5%.
Function Call Optimization: Fully optimized across function calls, timing, and parameter selection, with test scores increasing from 49.7% in previous models to 66.5%.
Image Input Support: Through the Realtime API, developers can add images, photos, and screenshots to a conversation, allowing the model to respond based on what the user sees.
Multilingual Support: The model significantly improves detection of alphanumeric sequences across languages, achieving 82.8% accuracy in reasoning tests.

Technical Principles of gpt-realtime

Single-Model Processing: Unlike traditional speech pipelines, gpt-realtime processes and generates audio directly with a single model, reducing latency and preserving subtle speech nuances for more natural, expressive responses.
Deep Learning and Training: Trained in close collaboration with customers, the model focuses on real-world tasks such as customer service, personal assistants, and education, ensuring better adaptability for developers building and deploying voice agents.
Multidimensional Optimization: Optimized across speech quality, intelligence, instruction-following, and function calling by improving model architecture and training methods, enhancing performance in real-world scenarios.
Asynchronous Function Calls: Improved asynchronous function calling allows long-running functions to execute without interrupting the conversation, letting the model maintain fluid dialogue while awaiting results.

Project Link

Official Website: https://openai.com/index/introducing-gpt-realtime/

Application Scenarios for gpt-realtime

Customer Service: Integrated into call centers to provide real-time solutions, improving efficiency and customer satisfaction.
Education: Helps students practice language pronunciation and expression, offering real-time feedback and corrections to enhance learning outcomes.
Personal Assistants: Embedded in smart speakers or smartphones to provide schedule management, information retrieval, device control, and other services.
Healthcare: Enables doctors to record patient notes in real time, improving efficiency and reducing manual entry time.
Entertainment: Used in voice-interactive games to create immersive experiences, allowing players to interact with game characters through speech.