AI Visibility Scorecard
Open Source AI
theopensource.ai · Technology
Borderline visible. AI bots can crawl Open Source AI, but the structured-data signals are thin - you are at real risk of being skipped when buyers ask ChatGPT, Claude, or Perplexity for a recommendation.
AI engines read this profile 9 times
Claude · ChatGPT · Apple Intelligence · Meta AI
#1,300,037 of 2,705,287 in Technology for AI visibility
<1
4
AEO Visibility
iBorderline · 4/10
85
Muse Index Score
iAI agent readiness
Transactable · 85/100
11
AI Adoption
iBasic · 11/100
About Open Source AI
from our crawl and measurement
"The ultimate platform for discovering, evaluating, and comparing 100+ open-source AI models including LLaMA 3, Mixtral, Qwen, Gemma. Features KYI™ benchmarking and unified ONE API." That is how Open Source AI introduces itself. When AI engines look at it, they find little to work with. It scores 4.0 out of 10.
On its own pages the site does well on structured data describing the business, a clear heading structure, crawler access and the files AI engines look for and sitemaps and entity links AI can follow. It is passable on a partly stated business identity. What holds it back is credibility markers like credentials or reviews.
Off the page there is only faint evidence that only a handful of sites link to it and the domain is only lightly established. Beyond that, AI engines do not yet recognise it as a distinct business, there is no press coverage to draw on, nobody is discussing it where AI engines look and it does not come up on Reddit. None of that can be fixed on the page: it has to be earned.
AI crawlers have visited 6 times in our tracking, including GPTBot (ChatGPT), ClaudeBot (Anthropic) and Applebot (Siri). The site links to no social profiles, so there is nothing tying the brand to a wider presence.
The 6 signals AI reads
Strong · Good · Fair · Weak
Structured Data
Strong
Organization / LocalBusiness JSON-LD that AI can read.
Content Structure
Strong
Clear headings and answer-style content.
Entity Clarity
Good
How clearly your brand identity reads to AI.
E-E-A-T Signals
Experience, Expertise, Authority, Trust
Weak
Experience, Expertise, Authority, Trust markers.
Technical AEO
Good
robots.txt, llms.txt, and AI-bot crawl access.
AI Discoverability
Strong
Sitemaps and entity links AI can follow.
Off-page authority
How the web signals your brand to AI
Backlinks
Weak
No inbound links found yet.
Domain Authority
Weak
Little domain authority yet.
Reference Presence
Weak
Not in AI knowledge graphs yet.
News & Press
Weak
No press coverage found yet.
Community
Weak
No community discussion yet.
Social Mentions
Weak
No social discussion found yet.
What this score means
Your AEO score measures whether AI search engines - ChatGPT, Claude, Perplexity, Gemini - can actually read your site and cite it in answers. Roughly two-thirds of sites are invisible to them. At 4/10, Open Source AI is crawlable but under-signaled - fixable, and the signals above are where to start.
Frequently Asked Questions
What are open source AI models?
Open source AI models are machine learning models whose source code, architecture, and weights are publicly available. They can be freely used, modified, and deployed without vendor lock-in, offering transparency and cost savings compared to proprietary alternatives.
How do I choose the best open source AI model for my project?
Consider your specific use case, required performance metrics, available compute resources, and licensing requirements. Our KYI benchmarking system evaluates models across speed, quality, and cost to help you make informed decisions. Start by browsing models in your category of interest.
Are open source AI models as good as proprietary ones like GPT-4?
Many open source models like LLaMA 3.1, Mixtral, and Qwen 2.5 now match or exceed proprietary models in specific tasks. While GPT-4 excels in general reasoning, open source alternatives offer comparable performance with benefits like data privacy, customization, and no usage limits.
Can I use open source AI models commercially?
Yes, most open source AI models can be used commercially, but always check the specific license. Popular licenses include Apache 2.0, MIT, and custom licenses like LLaMA's community license. Our model pages clearly display licensing information for each model.
How much does it cost to run open source AI models?
Costs vary based on model size and infrastructure. Small models (7B parameters) can run on consumer GPUs, while large models (70B+) require enterprise hardware. Cloud hosting typically costs $0.50-$5 per million tokens. Self-hosting eliminates per-token costs but requires upfront hardware investment.
Is this your brand?
The exact fixes for Open Source AI
Which AI engines already crawl you
Free AI bot monitoring: see every AI crawler that visits you
Already have an account? Sign in
How to Get Your Brand Cited by ChatGPT, Gemini, and Claude: The Complete AEO Guide
The search landscape has fundamentally shifted. While Google still dominates, millions of users now ask questions to ChatGPT, Gemini, and Claude instead of typing into a search bar.
Continue reading in your free Engagemii portalFree signup unlocks the full article plus your personalized AEO fix list for Open Source AI.
Source & Attribution
Scored by Engagemii on July 31, 2026. Methodology: engagemii.com/aeo/methodology
Source URL: https://engagemii.com/aeo/brands/theopensource-ai
Cite this score: Engagemii (2026). "AEO Score for Open Source AI." Retrieved from https://engagemii.com/aeo/brands/theopensource-ai
Licensed under CC BY 4.0. You may reuse this data with attribution: a visible link to engagemii.com.
Powered by Engagemii - The Answer Engine Optimization (AEO) Platform