Flux is the first conversational speech recognition model specifically designed for voice agents, addressing the common challenge of turn detection without the need for separate systems like voice activity detectors. It integrates turn detection into the same model that handles transcription, reducing latency and improving accuracy, enabling seamless conversational flow with less risk of interruptions or robotic pauses. The model offers Nova-3 level transcription quality, maintaining word error rates comparable to leading models while delivering real-time conversational intelligence. Flux's architecture simplifies development by replacing complex pipelines with a single API that manages conversation-native events, making it easier for developers to create natural and responsive voice agents. Additionally, the model's configurability allows developers to optimize performance according to specific use cases, and its effectiveness has been demonstrated through benchmarks and real-world scenarios, providing an innovative solution to longstanding issues in voice AI.