Pipecat vs Sesame

Comparing the features of Pipecat to Sesame

Feature
Pipecat
Sesame

Capability Features

Community Support
Consistent Personality
Context Awareness
Conversational Dynamics
Conversational Speech Generation
Daily.co Engineering Support
Dataset Size
1 million hours
Documentation Provided
Emotional Intelligence
Evaluation Suite
Model Sizes
Tiny: 1B backbone, 100M decoderSmall: 3B backbone, 250M decoderMedium: 8B backbone, 300M decoder
Multimodal Conversational AI
Multiple Speaker Handling
Objective Metrics
Word Error RateSpeaker SimilarityHomograph DisambiguationPronunciation Consistency
Open Source
Apache 2.0
Partial Multilingual Support Planned
Planned for 20+ languages
Pronunciation Correction
Sequence Length
2048
Single-Stage Model
Subjective Metrics
Comparative Mean Opinion Score
Text and Audio Input
TextAudio
Training Epochs
5
Voice Conversational AI

Integration Features

Discord Community
GitHub Release
Github Repository
LLama Architecture Backbone
Mimi Split-RVQ Tokenizer

Limitation Features

Cannot Model Conversation Structure
English Language Dominance
Memory Bottleneck in Training
No Pre-trained Language Model Use
Real-Time Generation Delay
RVQ time-to-first-audio scales poorly

Pricing Features

Free Preview