Handy vs Sesame

Comparing the features of Handy to Sesame

Feature
Handy
Sesame

Capability Features

Consistent Personality
Context Awareness
Conversational Dynamics
Conversational Speech Generation
Cross Platform
Customizable Key Bindings
Dataset Size
1 million hours
Emotional Intelligence
Evaluation Suite
Keyboard Shortcut Activation
Model Sizes
Tiny: 1B backbone, 100M decoderSmall: 3B backbone, 250M decoderMedium: 8B backbone, 300M decoder
Multiple Speaker Handling
Objective Metrics
Word Error RateSpeaker SimilarityHomograph DisambiguationPronunciation Consistency
Open Source
Apache 2.0
Partial Multilingual Support Planned
Planned for 20+ languages
Private Local Processing
Pronunciation Correction
Push To Talk
Sequence Length
2048
Single-Stage Model
Speech-to-Text
Subjective Metrics
Comparative Mean Opinion Score
Text and Audio Input
TextAudio
Toggle Transcription Mode
Training Epochs
5

Integration Features

GitHub Release
LLama Architecture Backbone
Mimi Split-RVQ Tokenizer
Other Platform Support
Windows Support

Limitation Features

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

Pricing Features

Free Preview
Free Tier