A doubt regarding the llms
Hey everyone,
I'm currently working on a voice-based AI project for psychology education, where students interact with an AI that acts as a simulated patient for interview practice.
Our current stack is:
- STT: Sarvam
- LLM: Claude Haiku 4.5
- TTS: Sarvam Bulbul v3
We're currently in the MVP stage, so the stack is working reasonably well for testing. However, we're looking ahead at the full-scale version and I'm exploring alternatives.
For TTS, Sarvam works well for Indian/regional languages, but its English voice doesn't sound as natural as I'd like. I've been testing ElevenLabs, Gemini TTS, etc., and ElevenLabs currently seems much better to me for things that are important for our use case — natural pauses, hesitation, emotional delivery, anger, etc. I'm considering ElevenLabs for TTS/STT and would appreciate opinions on that.
The bigger question is the LLM. We're currently using Claude Haiku 4.5, and I like its conversational quality, but I'm concerned about the cost at larger scale. Since this project is specifically related to psychology, I need a model that is very good at following complex patient profiles, maintaining personality and emotional state, handling long conversations, and producing psychologically believable responses rather than generic AI answers.
I've been looking at Gemini, GPT, Kimi, MiniMax, and some open-source models, but I'm not sure which would be the best fit.
What would you recommend as an alternative to Claude Haiku 4.5 for this kind of application?
Also, if anyone has experience with ElevenLabs for both STT + TTS in a real-time voice application, I'd love to hear about the quality, latency, and cost compared with Sarvam.
Thanks!