REPOGEO REPORT · LITE

continuedev/what-llm-to-use

Default branch main · commit 3c7cb09e · scanned 5/29/2026, 10:47:58 PM

GitHub: 651 stars · 37 forks

AI VISIBILITY SCORE

27 /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

1 / 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 continuedev/what-llm-to-use, 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 clearly state its purpose as an LLM comparison guide.

Why:

CURRENT

# What LLM to use? A perspective from the DevAI space

With how fast things are moving in the DevAI space, a shorthand for the community of developers building software with the help of large language models (LLMs), it can be challenging to figure out which model to use.

COPY-PASTE FIX

# What LLM to use? A comprehensive guide for DevAI

This repository is a comprehensive, developer-focused guide and comparison tool to help you choose the right Large Language Model (LLM) for your coding projects, navigating the fast-moving DevAI space.

mediumabout#2

Expand the repository description to be more explicit about its function.

Why:

CURRENT

👀 What LLM to use?

COPY-PASTE FIX

A comprehensive, developer-focused guide and comparison of Large Language Models (LLMs) to help you choose the best one for your coding projects.

mediumtopics#3
Add more specific topics to clarify the repository's function as a guide and comparison.
Why:
CURRENT
```
ai, dev, llm
```
COPY-PASTE FIX
```
ai, dev, llm, llm-comparison, llm-guide, model-selection, generative-ai, developer-tools
```

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 continuedev/what-llm-to-use

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

OpenAI GPT-4

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

OpenAI GPT-4 · recommended 1×
Google Gemini 1.5 Pro · recommended 1×
GitHub Copilot · recommended 1×
Amazon CodeWhisperer · recommended 1×
Mistral Large · recommended 1×

CATEGORY QUERY
What factors should I consider when choosing an LLM for my coding project?
you: not recommended
AI recommended (in order):
1. OpenAI GPT-4
2. Google Gemini 1.5 Pro
3. GitHub Copilot
4. Amazon CodeWhisperer
5. Mistral Large
6. Anthropic Claude 3 Opus
7. Meta Llama 3
8. Mistral 7B
9. Mixtral 8x7B Instruct
10. Code Llama
11. OpenAI GPT-4 Turbo
12. OpenAI Fine-tuning API
13. GPT-3.5 Turbo
AI recommended 13 alternatives but never named continuedev/what-llm-to-use. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Which large language models are best for open-source versus commercial development?
you: not recommended
AI recommended (in order):
1. Llama 3
2. Mistral 7B / Mixtral 8x7B
3. Gemma
4. Falcon
5. Llama 2
6. GPT-4 / GPT-4o
7. Claude 3 Opus / Sonnet / Haiku
8. Gemini 1.5 Pro / Flash
9. Cohere Command R+ / Command R
10. Azure OpenAI Service
AI recommended 10 alternatives but never named continuedev/what-llm-to-use. 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 continuedev/what-llm-to-use?
pass
AI did not name continuedev/what-llm-to-use — 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 continuedev/what-llm-to-use in production, what risks or prerequisites should they evaluate first?
pass
AI named continuedev/what-llm-to-use 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 continuedev/what-llm-to-use solve, and who is the primary audience?
pass
AI did not name continuedev/what-llm-to-use — 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?

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Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite