LLaMA-Omni vs awesome-llm-apps
A neutral, constraint-first comparison - live GitHub stats and typed relationships, not marketing.
| LLaMA-Omni | awesome-llm-apps | |
|---|---|---|
| Tagline | LLaMA-Omni is a speech interaction model built upon Llama-3.1-8B-Instruct, allowing for seamless low-latency speech-to-speech and speech-to-text interactions. | 100+ AI Agent & RAG apps you can actually run — clone, customize, ship. |
| Stars | 3.1k | 117k |
| Forks | 223 | 17k |
| Open issues | 52 | 6 |
| Language | Python | Python |
| License | Apache-2.0 | Apache-2.0 |
| Last pushed | May 19, 2025 | Jun 15, 2026 |
| Categories | Speech & Audio | AI Agents, LLM Frameworks |
LLaMA-Omni
This repository contains the source code for LLaMA-Omni, an innovative end-to-end speech interaction system that generates both text and speech responses based on speech inputs, with a latency as low as 226ms. It features advanced training techniques and is available in varying parameter sizes.
Python
awesome-llm-apps
A repository containing a collection of AI agent and Retrieval-Augmented Generation (RAG) applications that are ready to be cloned, customized, and deployed. The projects cover various aspects such as AI agents, always-on agents, multi-agent teams, RAG techniques, voice agents, fine-tuning for specific use cases, and more.
Python