REPOGEO REPORT · LITE

turboderp-org/exllamav3

Default branch master · commit 1d71227a · scanned 5/29/2026, 1:06:52 PM

GitHub: 907 stars · 103 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 turboderp-org/exllamav3, 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

hightopics#1

Add relevant topics to the repository

Why:

COPY-PASTE FIX

llm, inference, quantization, gpu, local-llm, openai-api, transformers, deep-learning, ai, machine-learning, python

highreadme#2

Reposition the README's opening sentence to highlight core differentiators

Why:

CURRENT

# ExLlamaV3

ExLlamaV3 is an inference library for running local LLMs on modern consumer GPUs. Headline features:

COPY-PASTE FIX

# ExLlamaV3

ExLlamaV3 is a highly optimized, low-VRAM inference library for running large, quantized language models on modern consumer GPUs. It leverages custom ExLlamaV3 quantization for high-performance local LLM inference, offering an OpenAI-compatible server via TabbyAPI. Headline features:

mediumhomepage#3
Add a homepage URL to the repository metadata
Why:
COPY-PASTE FIX
```
https://turboderp-org.github.io/exllamav3/
```

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 turboderp-org/exllamav3

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

llama.cpp

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

llama.cpp · recommended 1×
Ollama · recommended 1×
oobabooga/text-generation-webui · recommended 1×
Hugging Face transformers · recommended 1×
bitsandbytes · recommended 1×

CATEGORY QUERY
What are efficient ways to run large language models on consumer-grade GPUs locally?
you: not recommended
AI recommended (in order):
1. llama.cpp
2. Ollama
3. text-generation-webui (oobabooga/text-generation-webui)
4. Hugging Face transformers
5. bitsandbytes
6. LM Studio
7. Jan
AI recommended 7 alternatives but never named turboderp-org/exllamav3. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Looking for an optimized library to perform local LLM inference with OpenAI API compatibility.
you: not recommended
AI recommended (in order):
1. Ollama (ollama/ollama)
2. LM Studio (lmstudio-ai/lmstudio)
3. LocalAI (go-skynet/LocalAI)
4. vLLM (vllm-project/vllm)
5. text-generation-inference (TGI) by Hugging Face (huggingface/text-generation-inference)
6. Llama.cpp (ggerganov/llama.cpp)
7. LiteLLM (BerriAI/litellm)
AI recommended 7 alternatives but never named turboderp-org/exllamav3. 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/exllamav3?
pass
AI named turboderp-org/exllamav3 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/exllamav3 in production, what risks or prerequisites should they evaluate first?
pass
AI named turboderp-org/exllamav3 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/exllamav3 solve, and who is the primary audience?
pass
AI named turboderp-org/exllamav3 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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MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/turboderp-org/exllamav3.svg)](https://repogeo.com/en/r/turboderp-org/exllamav3)

HTML

<a href="https://repogeo.com/en/r/turboderp-org/exllamav3"><img src="https://repogeo.com/badge/turboderp-org/exllamav3.svg" alt="RepoGEO" /></a>

Pro

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turboderp-org/exllamav3 — 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