Why Choosing the Right LLM Matters in Conversational AI
For Voice AI and Chat AI, model performance is rarely one-size-fits-all. The right choice depends on:
- Latency requirements (critical in real-time TTS/STT for voice agents)
- Instruction following & tool calls (some models regress here)
- Cost sensitivity at scale
- Prompt adaptability (older prompts often fail without re-tuning)
For example, when some of our customers moved from GPT-4o to Gemini, costs and overall conversational quality improved, but tool calls fared poorly — a reminder that every LLM change comes with tradeoffs.
This is why systematic evaluation, simulation, and QA pipelines are essential before any migration.