REPOGEO REPORT · LITE

VITA-MLLM/VITA-Audio

Default branch main · commit 0abaf17e · scanned 6/9/2026, 9:08:00 PM

GitHub: 680 stars · 62 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE

28 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

1 pass · 1 warn · 0 fail

Objective metadata checks

AI knows your name

2 / 3

Direct prompts that named your repo

HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface VITA-MLLM/VITA-Audio, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION

hightopics#1

Add relevant topics to the repository

Why:

COPY-PASTE FIX

speech-language-model, multimodal-ai, audio-generation, speech-synthesis, asr, tts, low-latency, efficient-ai, neurips-2025

highreadme#2

Add a concise project summary paragraph to the README

Why:

CURRENT

<p align="center">
    
</p>

<font size=7><div align='center' > [📖 VITA-Audio Paper] [🤖 Model Weight]  [[💬 WeChat (微信)](./asset/wechat-group.jpg)]</div></font>

## :fire: News

COPY-PASTE FIX

VITA-Audio is a cutting-edge, open-source large speech-language model designed for fast, interleaved cross-modal token generation. It achieves significant inference speedups (3-5x) and ultra-low latency (53ms for first audio token) for real-time audio-text applications, setting new benchmarks in ASR, TTS, and SQA.

<p align="center">
    
</p>

<font size=7><div align='center' > [📖 VITA-Audio Paper] [🤖 Model Weight]  [[💬 WeChat (微信)](./asset/wechat-group.jpg)]</div></font>

## :fire: News

mediumhomepage#3
Add the paper URL as the repository homepage
Why:
COPY-PASTE FIX
```
[Insert actual URL for the VITA-Audio paper here]
```

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall

0 / 2

0% of queries surface VITA-MLLM/VITA-Audio

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Whisper

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

Whisper · recommended 1×
microsoft/onnxruntime · recommended 1×
NVIDIA/TensorRT · recommended 1×
NVIDIA/NeMo · recommended 1×
Google Conformer-Transducer · recommended 1×

CATEGORY QUERY
Looking for an efficient large speech model with very low inference latency for real-time applications.
you: not recommended
AI recommended (in order):
1. Whisper
2. ONNX Runtime (microsoft/onnxruntime)
3. TensorRT (NVIDIA/TensorRT)
4. NVIDIA NeMo (NVIDIA/NeMo)
5. Google Conformer-Transducer
6. Facebook Wav2Vec 2.0
7. Hugging Face transformers (huggingface/transformers)
8. Hugging Face optimum (huggingface/optimum)
9. Google Speech-to-Text API
10. Amazon Transcribe
11. AssemblyAI
AI recommended 11 alternatives but never named VITA-MLLM/VITA-Audio. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are the best open-source end-to-end speech generation models for cross-modal tasks?
you: not recommended
AI recommended (in order):
1. VALL-E X
2. Meta Voice (V2)
3. Bark
4. Coqui TTS
5. XTTS v2
6. YourTTS
7. StyleTTS 2
AI recommended 7 alternatives but never named VITA-MLLM/VITA-Audio. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
warn
Suggestion:
README presence
pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

Compared to common alternatives in this category, what is the core differentiator of VITA-MLLM/VITA-Audio?
pass
AI did not name VITA-MLLM/VITA-Audio — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts VITA-MLLM/VITA-Audio in production, what risks or prerequisites should they evaluate first?
pass
AI named VITA-MLLM/VITA-Audio explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
In one sentence, what problem does the repo VITA-MLLM/VITA-Audio solve, and who is the primary audience?
pass
AI named VITA-MLLM/VITA-Audio explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of VITA-MLLM/VITA-Audio. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/VITA-MLLM/VITA-Audio.svg)](https://repogeo.com/en/r/VITA-MLLM/VITA-Audio)

HTML

<a href="https://repogeo.com/en/r/VITA-MLLM/VITA-Audio"><img src="https://repogeo.com/badge/VITA-MLLM/VITA-Audio.svg" alt="RepoGEO" /></a>

Pro

Subscribe to Pro for deep diagnoses

VITA-MLLM/VITA-Audio — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite