Which is more popular, agents or AudioGPT?

agents has more GitHub stars (14,454 vs 10,167).

Which is more actively developed, agents or AudioGPT?

agents had more commits in the last 90 days (532 vs 0).

Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.

Side-by-side comparison of two AI agent tools

AudioGPT has had no commit in 41 months; agents is actively maintained (532 commits in the last 90 days).
agents is growing faster: +1,352 GitHub stars in the last 30 days vs +-7 for AudioGPT.
Pick agents for: a framework for building realtime voice AI agents. Pick AudioGPT for: audioGPT: Understanding and Generating Speech, Music, Sound, and Talking Head.

From GitHub data refreshed daily.

agentsopen-source

A framework for building realtime voice AI agents 🤖🎙️📹

AudioGPT: Understanding and Generating Speech, Music, Sound, and Talking Head

+Comprehensive multi-modal capabilities with flexible integrations for STT, LLM, TTS, and Realtime APIs in a single framework
+Built-in telephony integration allows agents to make and receive phone calls through LiveKit's telephony stack
+Advanced semantic turn detection using transformer models helps reduce interruptions and improve conversation flow

+Comprehensive multimodal coverage spanning speech, singing, general audio, and visual-audio tasks in one unified framework
+Integrates multiple proven foundation models like Whisper, VITS, and DiffSinger with pretrained weights available
+Open source implementation with active research backing and Hugging Face demo for immediate experimentation

-Requires server infrastructure and technical expertise to deploy and maintain realtime voice agents
-Complex setup with multiple integration points may have a steep learning curve for newcomers
-Real-time voice processing demands significant computational resources and low-latency networking

-Many features marked as Work in Progress indicating incomplete implementation and potential instability
-Complex setup requiring multiple model dependencies and not all referenced models have available repositories
-Research-focused platform may lack production-ready documentation and enterprise support

•Customer service automation with voice-enabled agents that can handle phone calls and web-based interactions
•Virtual assistants for healthcare or education that need to see, hear, and respond in real-time conversations
•Interactive voice response (IVR) systems that integrate with existing telephony infrastructure for business applications

•Content creators and podcasters needing text-to-speech synthesis, voice style transfer, and audio enhancement for multimedia production
•Audio researchers developing new models who need a comprehensive baseline framework integrating multiple audio AI capabilities
•Application developers building voice assistants, audio games, or accessibility tools requiring speech recognition, synthesis, and audio processing

Which is more popular, agents or AudioGPT?: agents has more GitHub stars (14,454 vs 10,167).
Which is more actively developed, agents or AudioGPT?: agents had more commits in the last 90 days (532 vs 0).
Should I use agents or AudioGPT?: Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.