RRepoGEO

REPOGEO REPORT · LITE

nebuly-ai/optimate

Default branch main · commit a6d302f9 · scanned 5/19/2026, 6:28:31 AM

GitHub: 8,345 stars · 620 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 nebuly-ai/optimate, 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
    Rewrite README introduction to highlight unique focus and reposition legacy status

    Why:

    CURRENT
    # OptiMate

**[Legacy]**

This repository is now in a legacy phase and is no longer actively maintained. Although the source code is still available in the Git history, there will be no additional updates or official support.

**[About Nebuly]**

Our team is fully committed on creating the best user-experience platform for LLMs so that companies can understand user behavior at scale when interacting with their LLM-based products. 
- To learn more on how to get started, visit our official documentation
- If you need enterprise support, please contact us here

**[About optimate]**

We have open-sourced a couple of internal projects to the community, but we are not currently maintaining them. Optimate is a collection of libraries designed to help you optimize your AI models. It is an open-source project developed by Nebuly AI but is **not actively maintained**.
    COPY-PASTE FIX
    # OptiMate

OptiMate is a collection of open-source libraries developed by Nebuly AI, designed to help you optimize your AI models. It offers tools like Speedster for inference cost reduction, Nos for maximizing Kubernetes GPU cluster utilization, and ChatLLaMA for fine-tuning optimization.

**[Legacy Status]**
Please note that this repository is in a legacy phase and is not actively maintained, though the source code remains available for reference. There will be no additional updates or official support.

**[About Nebuly]**
Our team is fully committed on creating the best user-experience platform for LLMs so that companies can understand user behavior at scale when interacting with their LLM-based products. 
- To learn more on how to get started, visit our official documentation
- If you need enterprise support, please contact us here
  • mediumtopics#2
    Add specific topics for Kubernetes and MLOps

    Why:

    CURRENT
    ai, analytics, artificial-intelligence, deeplearning, large-language-models, llm
    COPY-PASTE FIX
    ai, analytics, artificial-intelligence, deeplearning, large-language-models, llm, kubernetes, mlops, gpu-optimization, infrastructure-optimization, resource-management
  • lowcomparison#3
    Add a comparison section to the README

    Why:

    COPY-PASTE FIX
    Add a new section to the README, for example, `## Comparison with Alternatives`, that briefly explains how OptiMate's focus on Kubernetes infrastructure (via `Nos`) differentiates it from model-level optimization tools like ONNX Runtime or TensorRT.

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 nebuly-ai/optimate
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. TensorFlow Lite · recommended 1×
  4. PyTorch Quantization · recommended 1×
  5. TensorFlow Model Optimization Toolkit · recommended 1×
  • CATEGORY QUERY
    How to reduce inference costs and improve performance for deep learning models?
    you: not recommended
    AI recommended (in order):
    1. TensorFlow Lite
    2. ONNX Runtime
    3. PyTorch Quantization
    4. TensorFlow Model Optimization Toolkit
    5. PyTorch Pruning
    6. Hugging Face Transformers
    7. PaddlePaddle
    8. MobileNet
    9. EfficientNet
    10. YOLOv5/v8
    11. NVIDIA TensorRT
    12. OpenVINO
    13. Apple Core ML
    14. PyTorch DataLoader
    15. TensorFlow tf.data

    AI recommended 15 alternatives but never named nebuly-ai/optimate. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking tools to optimize large language model inference on various hardware platforms.
    you: not recommended
    AI recommended (in order):
    1. NVIDIA TensorRT
    2. OpenVINO Toolkit
    3. ONNX Runtime
    4. DeepSpeed-MII
    5. vLLM
    6. TVM (Apache TVM)
    7. Triton Inference Server
    8. TorchServe

    AI recommended 8 alternatives but never named nebuly-ai/optimate. 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 nebuly-ai/optimate?
    pass
    AI named nebuly-ai/optimate explicitly

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

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

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

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