RRepoGEO

REPOGEO REPORT · LITE

imoneoi/openchat

Default branch master · commit 47a35961 · scanned 5/14/2026, 5:46:12 AM

GitHub: 5,484 stars · 434 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 imoneoi/openchat, 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 to highlight deployability on consumer GPUs

    Why:

    CURRENT
    OpenChat is an innovative library of **open-source language models**, fine-tuned with **C-RLFTa strategy inspired by offline reinforcement learning.
    - Our models learn from mixed-quality data without preference labels, delivering exceptional performance on par with `ChatGPT`, even with a `7B` model which can be run on a **consumer GPU (e.g. RTX 3090)**.
    COPY-PASTE FIX
    OpenChat provides **high-performing open-source language models** designed for practical deployment, including on **consumer GPUs (e.g., RTX 3090)**. Our models are fine-tuned with C-RLFT, an offline reinforcement learning strategy, to learn from mixed-quality data without preference labels, delivering exceptional performance on par with `ChatGPT`.
  • mediumtopics#2
    Add more specific topics to improve categorization

    Why:

    CURRENT
    large-language-models, open-source, transformers
    COPY-PASTE FIX
    large-language-models, open-source, transformers, llm-models, instruction-tuning, chat-models, consumer-gpu-llm
  • lowabout#3
    Refine the 'About' description for clarity and impact

    Why:

    CURRENT
    OpenChat: Advancing Open-source Language Models with Imperfect Data
    COPY-PASTE FIX
    OpenChat delivers high-performing, open-source language models that rival commercial LLMs, fine-tuned efficiently with mixed-quality data for practical deployment.

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 imoneoi/openchat
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ggerganov/llama.cpp
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. ggerganov/llama.cpp · recommended 1×
  2. ollama/ollama · recommended 1×
  3. vllm-project/vllm · recommended 1×
  4. huggingface/transformers · recommended 1×
  5. TimDettmers/bitsandbytes · recommended 1×
  • CATEGORY QUERY
    How can I deploy a high-performing open-source large language model on a consumer GPU?
    you: not recommended
    AI recommended (in order):
    1. llama.cpp (ggerganov/llama.cpp)
    2. Ollama (ollama/ollama)
    3. vLLM (vllm-project/vllm)
    4. Hugging Face transformers (huggingface/transformers)
    5. bitsandbytes (TimDettmers/bitsandbytes)
    6. ExLlamaV2 (turboderp/exllamav2)

    AI recommended 6 alternatives but never named imoneoi/openchat. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for an open-source LLM that performs like commercial models without preference data.
    you: not recommended
    AI recommended (in order):
    1. Llama 3
    2. Mixtral 8x7B
    3. Gemma
    4. Mistral 7B
    5. Qwen
    6. Falcon

    AI recommended 6 alternatives but never named imoneoi/openchat. 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 imoneoi/openchat?
    pass
    AI named imoneoi/openchat explicitly

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

  • If a team adopts imoneoi/openchat in production, what risks or prerequisites should they evaluate first?
    pass
    AI named imoneoi/openchat 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 imoneoi/openchat solve, and who is the primary audience?
    pass
    AI named imoneoi/openchat 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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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite