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Inbox AI
Compared to Sesame
Inbox AI vs Sesame
Comparing the features of Inbox AI to Sesame
Feature
Inbox AI
Sesame
Capability Features
Connect to User's Information
Consistent Personality
Context Awareness
Conversational AI
Conversational Dynamics
Conversational Speech Generation
Dataset Size
1 million hours
Email Processing
Emotional Intelligence
Evaluation Suite
Information Capture
Model Sizes
Tiny: 1B backbone, 100M decoder
Small: 3B backbone, 250M decoder
Medium: 8B backbone, 300M decoder
Multiple Speaker Handling
Objective Metrics
Word Error Rate
Speaker Similarity
Homograph Disambiguation
Pronunciation Consistency
Partial Multilingual Support Planned
Planned for 20+ languages
Pronunciation Correction
Sequence Length
2048
Single-Stage Model
Subjective Metrics
Comparative Mean Opinion Score
Task Automation
Text and Audio Input
Text
Audio
Training Epochs
5
Voice Driven Automation
Integration Features
GitHub Release
LLama Architecture Backbone
macOS Compatibility
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
Open Source
Apache 2.0