RRepoGEO

REPOGEO REPORT · LITE

Alpha-VLLM/Lumina-T2X

Default branch main · commit 1c606962 · scanned 5/28/2026, 9:13:56 PM

GitHub: 2,252 stars · 95 forks

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 Alpha-VLLM/Lumina-T2X, 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
    Strengthen README's opening to emphasize 'unified framework' and 'any modality'

    Why:

    CURRENT
    The current README starts with a technical title and then many badges/links, potentially obscuring the core value proposition.
    COPY-PASTE FIX
    Insert the following sentence directly after the main H1 title: 'This repository provides a comprehensive, open-source framework for researchers and developers to build and experiment with text-to-any-modality generative models, including images, video, audio, and 3D content.'
  • mediumhomepage#2
    Add a project homepage URL

    Why:

    COPY-PASTE FIX
    Set the 'Homepage' field in the repository settings to the project's official website, a dedicated landing page, or a comprehensive Hugging Face Space if one exists for the entire Lumina-T2X project (e.g., `https://huggingface.co/spaces/Alpha-VLLM/Lumina-Next-T2I` if it serves as the primary project hub, or a more general project page).
  • mediumtopics#3
    Expand topics to include specific modalities and 'multimodal'

    Why:

    CURRENT
    aigc, diffusion, diffusion-model, diffusion-models, diffusion-transformer, generation-models, transformer, transformers
    COPY-PASTE FIX
    aigc, diffusion, diffusion-model, diffusion-models, diffusion-transformer, generation-models, transformer, transformers, multimodal, text-to-image, text-to-video, text-to-audio, text-to-3d, generative-ai

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 Alpha-VLLM/Lumina-T2X
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
RunwayML
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. RunwayML · recommended 1×
  2. Midjourney · recommended 1×
  3. DALL-E 3 · recommended 1×
  4. Stable Diffusion · recommended 1×
  5. Deforum Stable Diffusion · recommended 1×
  • CATEGORY QUERY
    How can I generate diverse content like images, video, and audio from text prompts?
    you: not recommended
    AI recommended (in order):
    1. RunwayML
    2. Midjourney
    3. DALL-E 3
    4. Stable Diffusion
    5. Deforum Stable Diffusion
    6. Pika Labs
    7. ElevenLabs
    8. Imagen Video
    9. AudioLM
    10. Make-A-Video
    11. AudioGen

    AI recommended 11 alternatives but never named Alpha-VLLM/Lumina-T2X. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What frameworks exist for text-to-multimodal generation using large diffusion transformers?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Diffusers
    2. OpenAI DALL-E 3
    3. Google Imagen
    4. Kandinsky
    5. CompVis/Latent Diffusion Models (LDMs)
    6. ControlNet
    7. SDXL (Stable Diffusion XL)

    AI recommended 7 alternatives but never named Alpha-VLLM/Lumina-T2X. 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 Alpha-VLLM/Lumina-T2X?
    pass
    AI named Alpha-VLLM/Lumina-T2X explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts Alpha-VLLM/Lumina-T2X in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Alpha-VLLM/Lumina-T2X 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 Alpha-VLLM/Lumina-T2X solve, and who is the primary audience?
    pass
    AI named Alpha-VLLM/Lumina-T2X explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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Alpha-VLLM/Lumina-T2X — 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