RRepoGEO

REPOGEO REPORT · LITE

hao-ai-lab/FastVideo

Default branch main · commit 30c45620 · scanned 5/17/2026, 3:12:01 AM

GitHub: 3,479 stars · 329 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
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 hao-ai-lab/FastVideo, 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 the README's opening sentence to emphasize specialization

    Why:

    CURRENT
    **FastVideo is a unified post-training and real-time inference framework for accelerated video generation.**
    COPY-PASTE FIX
    **FastVideo is the unified post-training and real-time inference framework *specifically engineered* for accelerated video generation, delivering unparalleled efficiency for diffusion models on a single GPU.**
  • mediumtopics#2
    Enhance repository topics with more specific keywords

    Why:

    CURRENT
    diffusers, diffusion-models, distillation, inference, post-training, video-generation
    COPY-PASTE FIX
    diffusers, diffusion-models, distillation, inference, post-training, video-generation, real-time-video-generation, gpu-acceleration, diffusion-model-inference, video-diffusion
  • lowreadme#3
    Add a 'Why FastVideo?' section to the README

    Why:

    COPY-PASTE FIX
    ## Why FastVideo?

Unlike general inference frameworks such as NVIDIA TensorRT, ONNX Runtime, or DeepSpeed, FastVideo is purpose-built for the unique challenges of video generation. We offer specialized optimizations for diffusion models to achieve real-time performance and unparalleled efficiency on single GPUs, specifically for video generation tasks.

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 hao-ai-lab/FastVideo
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ONNX Runtime
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ONNX Runtime · recommended 2×
  2. NVIDIA TensorRT · recommended 2×
  3. DeepSpeed · recommended 1×
  4. PyTorch 2.0 · recommended 1×
  5. xFormers · recommended 1×
  • CATEGORY QUERY
    How to accelerate video generation inference for diffusion models on a single GPU?
    you: not recommended
    AI recommended (in order):
    1. DeepSpeed
    2. PyTorch 2.0
    3. ONNX Runtime
    4. NVIDIA TensorRT
    5. xFormers
    6. FlashAttention
    7. torch.autocast

    AI recommended 7 alternatives but never named hao-ai-lab/FastVideo. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a framework for optimizing and deploying real-time video generation models efficiently.
    you: not recommended
    AI recommended (in order):
    1. NVIDIA TensorRT
    2. OpenVINO
    3. ONNX Runtime
    4. Apache TVM
    5. TorchScript
    6. TensorFlow Lite

    AI recommended 6 alternatives but never named hao-ai-lab/FastVideo. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 hao-ai-lab/FastVideo?
    pass
    AI named hao-ai-lab/FastVideo explicitly

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

  • If a team adopts hao-ai-lab/FastVideo in production, what risks or prerequisites should they evaluate first?
    pass
    AI named hao-ai-lab/FastVideo 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 hao-ai-lab/FastVideo solve, and who is the primary audience?
    pass
    AI named hao-ai-lab/FastVideo explicitly

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

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hao-ai-lab/FastVideo — 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