GPT Realtime Mini vs Gemini 3.5 Flash for 500 Hours Audio Monthly

For legal teams scaling meeting intelligence, the choice between real-time streaming and multimodal batch analysis defines your architecture. GPT Realtime Mini excels in latency-sensitive applications, providing a native speech-to-speech feedback loop ideal for conversational voice agents. Its architecture is purpose-built for scenarios where the immediate user experience of a voice assistant is the primary driver. In contrast, Gemini 3.5 Flash provides a robust multimodal alternative, particularly effective when you need to ingest dense, hour-long audio files for comprehensive summarization and extraction. While it also handles audio natively, its strength lies in long-horizon reasoning and its ability to process complex multimodal inputs (like synced video or screen shares) alongside audio. If your pipeline relies on asynchronous processing of recorded legal consultations, Gemini’s throughput and handling of large-scale context often prove more advantageous for generating high-fidelity structured notes. However, if your goal is an interactive tool that captures notes during live testimony or client interactions, the low-latency streaming capabilities of the Realtime-Mini series provide a distinct advantage. Engineers should evaluate whether their workload prioritizes immediate, conversational feedback—where model speed and streaming protocols are paramount—or the rigorous, multi-step analysis of existing meeting logs where context retention and reasoning accuracy are the core requirements.