REPOGEO REPORT · LITE

ngxson/wllama

Default branch master · commit 766d28e0 · scanned 6/22/2026, 10:07:09 AM

GitHub: 1,124 stars · 99 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

33 /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

2 / 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 ngxson/wllama, 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 H1 and opening sentence to highlight core value

Why:

CURRENT

# wllama - Wasm binding for llama.cpp

WebAssembly binding for llama.cpp

COPY-PASTE FIX

# wllama: Run Llama 2, Multimodal, and Tool-Calling LLMs Directly in Your Web Browser with WebAssembly & WebGPU

wllama provides a high-performance WebAssembly binding for llama.cpp, enabling client-side inference of large language models, including multimodal and tool-calling capabilities, directly in the browser.

hightopics#2

Expand topics with user-centric keywords for browser-based LLMs and features

Why:

CURRENT

llama, llamacpp, llm, wasm, webassembly

COPY-PASTE FIX

llama, llamacpp, llm, wasm, webassembly, browser-llm, web-llm, client-side-llm, webgpu, multimodal-ai, tool-calling, javascript, typescript, gguf

mediumreadme#3

Add a 'Comparison with Alternatives' section to clarify differentiators

Why:

COPY-PASTE FIX

Add a new section titled 'Comparison with Alternatives' or 'Why wllama?' in the README. This section should briefly highlight wllama's unique focus on llama.cpp's GGUF format, direct WebGPU/WebAssembly execution, and built-in multimodal/tool-calling support, contrasting it with broader frameworks or API clients.

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 ngxson/wllama

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

huggingface/transformers.js

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

huggingface/transformers.js · recommended 1×
mlc-ai/web-llm · recommended 1×
microsoft/onnxruntime-web · recommended 1×
tensorflow/tfjs · recommended 1×
pyodide/pyodide · recommended 1×

CATEGORY QUERY
How to run large language models directly in the browser using WebAssembly?
you: not recommended
AI recommended (in order):
1. Transformers.js (huggingface/transformers.js)
2. Web LLM (mlc-ai/web-llm)
3. ONNX Runtime Web (microsoft/onnxruntime-web)
4. TensorFlow.js (tensorflow/tfjs)
5. Pyodide (pyodide/pyodide)
6. WasmEdge (WasmEdge/WasmEdge)
AI recommended 6 alternatives but never named ngxson/wllama. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Looking for a library to integrate multimodal LLMs with tool calling into web apps.
you: not recommended
AI recommended (in order):
1. LangChain.js (langchain-ai/langchainjs)
2. LlamaIndex.TS (run-llama/LlamaIndexTS)
3. OpenAI JavaScript SDK (openai/openai-node)
4. Google AI JavaScript SDK (google/generative-ai-js)
5. Hugging Face Transformers.js (xenova/transformers.js)
6. Axios (axios/axios)
AI recommended 6 alternatives but never named ngxson/wllama. 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 ngxson/wllama?
pass
AI did not name ngxson/wllama — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts ngxson/wllama in production, what risks or prerequisites should they evaluate first?
pass
AI named ngxson/wllama 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 ngxson/wllama solve, and who is the primary audience?
pass
AI named ngxson/wllama 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/ngxson/wllama.svg)](https://repogeo.com/en/r/ngxson/wllama)

HTML

<a href="https://repogeo.com/en/r/ngxson/wllama"><img src="https://repogeo.com/badge/ngxson/wllama.svg" alt="RepoGEO" /></a>

Pro

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ngxson/wllama — 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