Mini-Omni

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1922 stars · 209 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Mini-Omni is an open-source multimodal large language model that performs real-time end-to-end speech-to-speech conversation with streaming audio output, without requiring separate ASR or TTS models. Mini-Omni2 extends it with vision and audio inputs and duplex interaction, aiming to be an open-source approximation of GPT-4o.

Use cases

• build a real-time voice chat assistant
• run speech-to-speech conversation without ASR/TTS pipelines
• stream audio responses from an LLM while it generates text
• add vision and audio understanding to a conversational model
• research multimodal speech language models
• batch audio-to-text and audio-to-audio inference

When to choose

• you need an open-source, self-hosted GPT-4o-like voice assistant
• you want low-latency streaming speech output from an LLM
• you are researching end-to-end speech language models
• English-only voice interaction is acceptable

When to avoid

• you need multilingual speech support (English only)
• you need production-grade, polished voice assistant infrastructure
• you lack GPU hardware for local inference
• you need high-accuracy ASR or TTS as standalone components

Facets

library · maturity experimental

speech-recognition tts llm-inference machine-learning chatbot artificial-intelligence large-language-models speech-processing python cross-platform speech-to-speech streaming-audio multimodal voice-assistant real-time-conversation gpt-4o-alternative natural-language-processing gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="gpt-omni/mini-omni2")