RRepoGEO

REPOGEO REPORT · LITE

Noeda/rllama

Default branch master · commit 1e1131fa · scanned 6/6/2026, 2:03:07 PM

GitHub: 554 stars · 32 forks

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 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 Noeda/rllama, 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
    Clarify project's core identity and independence in README's opening

    Why:

    CURRENT
    # RLLaMA
    
    RLLaMA is a pure Rust implementation of LLaMA large language model inference..
    COPY-PASTE FIX
    # RLLaMA
    
    RLLaMA is a *standalone, pure Rust implementation* of LLaMA large language model inference, *developed independently and not a binding to `llama.cpp` or an R library*.
  • hightopics#2
    Add relevant topics for discoverability

    Why:

    COPY-PASTE FIX
    rust, llama, llm, inference, opencl, avx2, gpu, cpu, machine-learning, deep-learning
  • mediumhomepage#3
    Add a homepage URL to the repository

    Why:

    COPY-PASTE FIX
    https://github.com/Noeda/rllama

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 Noeda/rllama
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
huggingface/candle
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. huggingface/candle · recommended 2×
  2. rustformers/llm-rs · recommended 1×
  3. LaurentMazare/tch-rs · recommended 1×
  4. rust-nlp/rust-bert · recommended 1×
  5. rustformers/ggml-rs · recommended 1×
  • CATEGORY QUERY
    How to run LLaMA models efficiently using Rust with GPU acceleration?
    you: not recommended
    AI recommended (in order):
    1. candle (huggingface/candle)
    2. llm-rs (rustformers/llm-rs)
    3. tch-rs (LaurentMazare/tch-rs)
    4. rust-bert (rust-nlp/rust-bert)
    5. ggml-rs (rustformers/ggml-rs)
    6. wgpu (gfx-rs/wgpu)

    AI recommended 6 alternatives but never named Noeda/rllama. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a Rust library to perform LLaMA inference leveraging AVX2 and OpenCL.
    you: not recommended
    AI recommended (in order):
    1. candle (huggingface/candle)
    2. llm (rust-llm/llm)
    3. tract (sonos/tract)
    4. rust-bert (huggingface/rust-bert)
    5. opencl-sys

    AI recommended 5 alternatives but never named Noeda/rllama. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    warn

    Suggestion:

  • 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 Noeda/rllama?
    pass
    AI named Noeda/rllama explicitly

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

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

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

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Noeda/rllama — 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