RRepoGEO

REPOGEO REPORT · LITE

mit-han-lab/distrifuser

Default branch main · commit 8aebdd6d · scanned 6/9/2026, 9:57:04 AM

GitHub: 726 stars · 34 forks

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 mit-han-lab/distrifuser, 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

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

OVERALL DIRECTION
  • mediumtopics#1
    Add more specific topics to improve categorization for distributed inference

    Why:

    CURRENT
    acceleration, diffusion-models, generative-ai, generative-model, parallelism
    COPY-PASTE FIX
    acceleration, diffusion-models, generative-ai, generative-model, parallelism, distributed-inference, multi-gpu, high-resolution-images, inference-optimization
  • lowreadme#2
    Add a 'Comparison' or 'Why DistriFusion?' section to the README

    Why:

    COPY-PASTE FIX
    ## Why DistriFusion?
While general distributed ML frameworks like PyTorch DDP, Hugging Face Accelerate, and DeepSpeed provide powerful tools for distributed training and inference, DistriFusion is specifically engineered for the unique challenges of high-resolution diffusion model inference. Our training-free algorithm focuses on optimizing patch interaction and communication to achieve significant acceleration without compromising image quality, a critical differentiator for generative AI applications.

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 mit-han-lab/distrifuser
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PyTorch Distributed Data Parallel (DDP)
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. PyTorch Distributed Data Parallel (DDP) · recommended 1×
  2. huggingface/accelerate · recommended 1×
  3. microsoft/DeepSpeed · recommended 1×
  4. huggingface/diffusers · recommended 1×
  5. NVIDIA/apex · recommended 1×
  • CATEGORY QUERY
    How to speed up high-resolution image generation with diffusion models across multiple GPUs?
    you: not recommended
    AI recommended (in order):
    1. PyTorch Distributed Data Parallel (DDP)
    2. Accelerate (huggingface/accelerate)
    3. DeepSpeed (microsoft/DeepSpeed)
    4. Hugging Face Diffusers Library (huggingface/diffusers)
    5. NVIDIA Apex (NVIDIA/apex)
    6. Ray (ray-project/ray)
    7. TensorFlow Distributed Strategy API
    8. JAX (google/jax)

    AI recommended 8 alternatives but never named mit-han-lab/distrifuser. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a method for distributed parallel inference to generate large diffusion model images efficiently.
    you: not recommended
    AI recommended (in order):
    1. RunDiffusion
    2. AWS SageMaker
    3. Hugging Face Accelerate
    4. Transformers library
    5. DeepSpeed
    6. PyTorch FSDP
    7. Google Cloud Vertex AI
    8. NVIDIA Triton Inference Server
    9. Ray Serve

    AI recommended 9 alternatives but never named mit-han-lab/distrifuser. 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 mit-han-lab/distrifuser?
    pass
    AI named mit-han-lab/distrifuser explicitly

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

  • If a team adopts mit-han-lab/distrifuser in production, what risks or prerequisites should they evaluate first?
    pass
    AI named mit-han-lab/distrifuser 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 mit-han-lab/distrifuser solve, and who is the primary audience?
    pass
    AI named mit-han-lab/distrifuser 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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mit-han-lab/distrifuser — 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