REPOGEO REPORT · LITE

VITA-MLLM/VITA

Default branch main · commit 35d064a6 · scanned 6/23/2026, 9:58:38 PM

GitHub: 2,520 stars · 182 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

35 /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

3 / 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, 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

highreadme#1

Reposition README opening to clearly state VITA-1.5 is an open-source model

Why:

COPY-PASTE FIX

VITA-1.5 is an open-source, real-time vision and speech interactive large multimodal model (LMM) designed for researchers and developers building advanced interactive AI applications.

mediumhomepage#2
Add a homepage URL to the repository metadata
Why:
COPY-PASTE FIX
```
https://vita-mllm.github.io/vita-1.5/
```

mediumreadme#3

Clarify the existing license in the README

Why:

COPY-PASTE FIX

Add a section or sentence in the README clarifying the specific terms of the existing LICENSE file, e.g., 'The code in this repository is released under the [specific license name/terms] as detailed in the LICENSE file.'

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

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Google Cloud AI Platform

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

Google Cloud AI Platform · recommended 1×
Vertex AI · recommended 1×
google/mediapipe · recommended 1×
Vertex AI Vision · recommended 1×
Google Cloud Speech-to-Text · recommended 1×

CATEGORY QUERY
How can I build applications with real-time vision, speech, and language interaction?
you: not recommended
AI recommended (in order):
1. Google Cloud AI Platform
2. Vertex AI
3. MediaPipe (google/mediapipe)
4. Vertex AI Vision
5. Google Cloud Speech-to-Text
6. Google Cloud Text-to-Speech
7. Google Cloud Natural Language API
8. Dialogflow ES
9. Dialogflow CX
10. Microsoft Azure AI Platform
11. Azure Cognitive Services for Vision
12. Computer Vision
13. Custom Vision
14. Azure Cognitive Services for Speech
15. Azure Cognitive Services for Language
16. Language Understanding (LUIS)
17. Text Analytics
18. QnA Maker
19. Azure Machine Learning
20. AWS AI Services
21. Amazon Rekognition
22. Amazon Transcribe
23. Amazon Polly
24. Amazon Comprehend
25. Amazon Lex
26. AWS Lambda
27. Amazon Kinesis
28. AWS Step Functions
29. OpenAI API
30. Google Cloud Vision
31. Azure Computer Vision
32. OpenAI Whisper
33. OpenAI TTS
34. GPT-4
35. GPT-3.5 Turbo
36. Hugging Face Transformers
37. OpenCV (opencv/opencv)
38. Hugging Face Model Hub
39. DETR
40. ViT
41. Bark
42. VITS
43. Transformers library (huggingface/transformers)
44. BERT
45. T5
46. Llama 2
47. DeepMotion
AI recommended 47 alternatives but never named VITA-MLLM/VITA. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Seeking an open-source omni-modal LLM for advanced real-time interactive applications.
you: not recommended
AI recommended (in order):
1. LLaVA
2. Fuyu-8B
3. BakLLaVA
4. CogVLM
5. MiniGPT-4 / MiniGPT-v2
AI recommended 5 alternatives but never named VITA-MLLM/VITA. 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?
pass
AI named VITA-MLLM/VITA explicitly
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 in production, what risks or prerequisites should they evaluate first?
pass
AI named VITA-MLLM/VITA 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 solve, and who is the primary audience?
pass
AI named VITA-MLLM/VITA explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

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MARKDOWN (README)

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

HTML

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

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VITA-MLLM/VITA — 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