RRepoGEO

REPOGEO REPORT · LITE

turboderp-org/exllamav2

Default branch master · commit 7dc12af3 · scanned 6/24/2026, 9:22:24 AM

GitHub: 4,565 stars · 338 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
57 /100
Needs work
Category recall
1 / 2
Avg rank #5.0 when recommended
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 turboderp-org/exllamav2, 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
  • highreadme#1
    Reposition the README's core value proposition to highlight high-throughput features

    Why:

    CURRENT
    ExLlamaV2 is an inference library for running local LLMs on modern consumer GPUs.
    COPY-PASTE FIX
    ExLlamaV2 is an advanced inference library designed for high-throughput, efficient execution of large language models (LLMs) locally on modern consumer GPUs, featuring dynamic batching, smart prompt caching, and K/V cache deduplication.
  • mediumhomepage#2
    Add a homepage link to the wiki

    Why:

    COPY-PASTE FIX
    https://github.com/turboderp-org/exllamav2/wiki

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
1 / 2
50% of queries surface turboderp-org/exllamav2
Avg rank
#5.0
Lower is better. #1 = top recommendation.
Share of voice
8%
Of all named tools, what % are you?
Top rival
vLLM
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. vLLM · recommended 2×
  2. llama.cpp · recommended 1×
  3. Transformers · recommended 1×
  4. bitsandbytes · recommended 1×
  5. TGI (Text Generation Inference) · recommended 1×
  • CATEGORY QUERY
    What are the best libraries for fast local LLM inference on consumer GPUs?
    you: #5
    AI recommended (in order):
    1. llama.cpp
    2. vLLM
    3. Transformers
    4. bitsandbytes
    5. ExLlamaV2 ← you
    6. TGI (Text Generation Inference)
    Show full AI answer
  • CATEGORY QUERY
    How to achieve high-throughput LLM inference locally with dynamic batching and caching?
    you: not recommended
    AI recommended (in order):
    1. vLLM
    2. TGI
    3. TensorRT-LLM
    4. DeepSpeed-MII
    5. Ollama
    6. Llama.cpp

    AI recommended 6 alternatives but never named turboderp-org/exllamav2. 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 turboderp-org/exllamav2?
    pass
    AI named turboderp-org/exllamav2 explicitly

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

  • If a team adopts turboderp-org/exllamav2 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named turboderp-org/exllamav2 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 turboderp-org/exllamav2 solve, and who is the primary audience?
    pass
    AI named turboderp-org/exllamav2 explicitly

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

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turboderp-org/exllamav2 — 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