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LLaMA-Omni

ictnlp/LLaMA-Omni

End-to-end speech interaction model based on Llama-3.1-8B-Instruct

GitHub Website

GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026

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3.1k stars225 forksLast push May 19, 2025 Python Apache-2.0

Decision brief

LLaMA-Omni is a specialized multimodal large language model tailored for enhancing speech interaction capabilities through advanced integration of speech-to-speech and speech-to-text functionalities.

Good fit when

- When targeting low-latency, high-quality end-to-end speech interactions that need to be performed in an academic research environment.
- If you are working on projects that require integrating both speech and text modalities for processing or generating responses, especially focusing on tasks where reducing latency is critical.

Avoid when

- Avoid LLaMA-Omni if your project requires commercial deployment since its usage rights are strictly non-commercial.
- If real-time interaction constraints are less critical than achieving high-quality speech output, another tool with more flexibility regarding latency and deployment options may be preferable.

Observed Jul 10, 2026 · Source: enrich:decision_facts

LLaMA-Omni alternatives Trust report

LLaMA-Omni vs ChatTTS

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Maintenance and security

Full trust report

Maintenance: Dormant (489d since push); As of Sep 20, 2026
Provenance: Not a fork · Organization account; As of Sep 20, 2026
Security (OSV): No lockfile; As of Jul 11, 2026

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

pip install LLaMA-Omni

PyPI

How it fits your stack(4)

Typed graph edges - alternatives, integrations, successors, and dependencies. Ranked by relationship type, not raw GitHub stars.

Alternative

ChatTTS

Both LLaMA-Omni and ChatTTS are generative speech models used for daily dialogue, but they have different model bases and focus areas.

alternative

whisper

Both LLaMA-Omni and Whisper deal with speech processing, but they serve different purposes. Whisper focuses on robust speech recognition, while LLaMA-Omni is about generating both text and speech responses from speech inputs.

nuclear

Although LLaMA-Omni focuses on speech interaction with large language models, the concept of finding free resources (in this case, music) and accessibility might be tangentially related to its overall utility in a resource-constrained environment.

awesome-generative-ai

LLaMA-Omni can be listed under the curated generative AI projects in awesome-generative-ai, given its focus on generating speech and text responses.

Relationship graph

Optional deeper exploration of typed edges and category neighbours.

Similar tools

Same-category neighbours not already linked as typed edges.

OmAgent

Build multimodal language agents for fast prototype and production

2.7k★

Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

LLaMA-Omni is designed for high-quality and low-latency speech interaction capabilities, aiming to achieve GPT-4o levelspeech functionalities.

Capability facts

Languages: python
Source: github.language+pyproject.toml · Sep 20, 2026

Graph entities

Smolagentsframework

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Sep 20, 2026)

conda create -n llama-omni python=3.10

Source link

README

Install 1. Clone this repository. 2. Install packages. 3. Install . 4. Install . Quick Start 1. Download the model from 🤗Huggingface. 2. Download the model. 3. Download the unit based HiFi GAN vocoder. LICENSE Our code is released under the Apache 2.0 License. Our model is inten...

For agents

This page has a .md twin and JSON over the API.

/tools/ictnlp-llama-omni.md GET /api/graphcanon/tools/ictnlp-llama-omni GET /api/graphcanon/graph?tool=ictnlp-llama-omni