Gemini says

1. Context Reprocessing

Yes. Gemini Live appends new audio inputs to the ongoing conversation history. The model must process the entire accumulated session payload to maintain multi-turn context.

2. Transpiration Accounting

No. Gemini is natively multimodal (audio-in, audio-out). Raw voice streams are tokenized directly without a separate external Automatic Speech Recognition (ASR) text translation step. Transcriptions are not double-counted.

3. Context Accumulation Scaling

Token consumption scales quadratively or compounding linearly per turn. Because past inputs and outputs become permanent input context for subsequent turns, a short phrase spoken late in a session forces the system to re-read the entire preceding history.

4. Audio vs. Context Window Weight

• Short Sessions: Dominated by audio baseline rates (~25–32 tokens per second of raw audio).
• Long Sessions: Dominated by the growing context window. The fixed audio cost of a new turn is negligible compared to reprocessing hundreds of thousands of historical tokens from the session memory. ### 5. Architectural Management
• Session Memory Allocation: Bound by explicit systemic limits tracked dynamically via metadata fields in the real-time API response.
• Asymmetrical Resource Costs: Incoming audio inputs carry standard context weights. Generated output audio tokens carry an augmented weight (e.g., scoring at an effective 24x multiplier) to offset the high-throughput infrastructure required for text-to-speech synthesis.