RRepoGEO

REPOGEO REPORT · LITE

oumi-ai/oumi

Default branch main · commit 5025b0f2 · scanned 6/28/2026, 9:26:31 AM

GitHub: 9,331 stars · 783 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 oumi-ai/oumi, 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 primary heading to clearly state core functionality

    Why:

    CURRENT
    ### Everything you need to build state-of-the-art foundation models, end-to-end
    COPY-PASTE FIX
    ### Oumi: The end-to-end platform to fine-tune, evaluate, and deploy open-source LLMs/VLMs
    
    Easily fine-tune, evaluate and deploy Gemma 4, Qwen3.5, Qwen3.6, gpt-oss, DeepSeek-R1, or any open source LLM / VLM!
  • mediumabout#2
    Enhance the repository description with key differentiators

    Why:

    CURRENT
    Easily fine-tune, evaluate and deploy Gemma 4, Qwen3.5, Qwen3.6, gpt-oss, DeepSeek-R1, or any open source LLM / VLM!
    COPY-PASTE FIX
    Oumi is a comprehensive, self-hostable, and privacy-centric platform to easily fine-tune, evaluate, and deploy Gemma 4, Qwen3.5, Qwen3.6, gpt-oss, DeepSeek-R1, or any open source LLM / VLM!
  • lowtopics#3
    Add broader, category-defining topics

    Why:

    CURRENT
    dpo, evaluation, fine-tuning, gpt-oss, gpt-oss-120b, gpt-oss-20b, inference, llama, llms, sft, slms, vlms
    COPY-PASTE FIX
    dpo, evaluation, fine-tuning, gpt-oss, gpt-oss-120b, gpt-oss-20b, inference, llama, llms, sft, slms, vlms, llm-ops, ai-framework, mlops-llm

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 oumi-ai/oumi
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
TRL
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. TRL · recommended 2×
  2. DeepSpeed · recommended 2×
  3. Hugging Face Ecosystem · recommended 1×
  4. Transformers · recommended 1×
  5. Accelerate · recommended 1×
  • CATEGORY QUERY
    What tools help fine-tune, evaluate, and deploy open-source large language models effectively?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Ecosystem
    2. Transformers
    3. Accelerate
    4. PEFT
    5. TRL
    6. Evaluate
    7. Inference Endpoints/Spaces
    8. MLflow
    9. Ray
    10. Ray Core
    11. Ray Train
    12. Ray Serve
    13. DeepSpeed
    14. VLLM
    15. Weights & Biases (W&B)
    16. Kubernetes
    17. KServe
    18. Seldon Core

    AI recommended 18 alternatives but never named oumi-ai/oumi. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a framework to fine-tune and serve custom large models using DPO or SFT methods.
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. TRL
    3. Text Generation Inference (TGI)
    4. vLLM
    5. Axolotl
    6. DeepSpeed
    7. Megatron-LM
    8. Ludwig
    9. LitGPT

    AI recommended 9 alternatives but never named oumi-ai/oumi. 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 oumi-ai/oumi?
    pass
    AI named oumi-ai/oumi explicitly

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

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

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

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oumi-ai/oumi — 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