pytorch.org 66 C
🛡️ SEO 47 🤖 GEO 72 ⚡ Perf 59 🏗️ Arch 93

pytorch.org — Global SEODiff Score 66/100

pytorch.org
📊

The AI-Readiness profile for pytorch.org is strong: an ACRI of 76/100 places it ahead of 83% of domains in the index. In the developer sector, pytorch.org outperforms the average (57), suggesting strong competitive positioning in AI search. Content is delivered server-side, meaning bots and AI agents can parse the full page without executing JavaScript. A 18.2× token bloat ratio means crawlers must process significantly more tokens to reach the actual content — a drag on extraction efficiency. The complete absence of JSON-LD schema is a missed opportunity: even basic Organization markup would improve how AI crawlers understand this domain. All major AI bot user-agents (GPTBot, ClaudeBot, CCBot, Google-Extended) are permitted by robots.txt, ensuring broad AI crawler access.

66
C — Global SEODiff Score
Comprehensive search visibility assessment
Strong foundations, but Traditional SEO (47) is your bottleneck.
🎯 Top Fix: Add Organization + WebSite JSON-LD → +5–8 pts
🔬 Automated SEODiff Assessment · Snapshot: Mar 20, 2026 · 📋 API
📈 ACRI Trend 19 snapshots
Feb 22 Mar 20
🔔 Recent AI Indexing Activity
🔄 Mar 20 Content change detected
🔄 Mar 18 Content change detected
🔄 Mar 16 Content change detected
🔄 Mar 10 Content change detected
Does your site score higher than pytorch.org?
Run the same 40-signal audit on your own domain — free, instant results.
Scan Your Site Free →
🧮 Score Transparency — How is this calculated?
🛡️ Traditional SEO (25% weight)47 × 0.25 = 11.8
🤖 AI Readiness / GEO (40% weight)72 × 0.40 = 28.8
⚡ Performance (20% weight)59 × 0.20 = 11.8
🏗️ Architecture & Trust (15% weight)93 × 0.15 = 13.9
Weighted sum = 11.8 + 28.8 + 11.8 + 13.9
Global SEODiff Score = 66 (C)
📊 ACRI Sub-Scores (AI Readiness Detail)
100
Bot Access
avg 92
100
Rendering
avg 93
60
Structure
avg 35
0
Schema
avg 9
85
Tech Stack
avg 63
🔀
Visibility Delta: Google vs AI
Google (Tranco)
Top 1%
Rank #13000
+16 pts
Gap
AI (ACRI)
Top 17%
Score 76/100

pytorch.org punches above its weight in AI — AI visibility exceeds Google ranking. This is a competitive moat worth protecting. ACRI measures technical crawler readiness. Read the methodology →

Why pytorch.org ranks here

Tech stackWordPress
Industrydeveloper
RenderingSSR
Schema coverage0 blocks
Token bloat18.2×

Fastest improvements

  • Add basic Organization and WebSite JSON-LD to fix “0 schema blocks” (see Schema Coverage).
  • Reduce token bloat (navigation/footer/code) so agents reach your main content faster (see Token Bloat).
  • Create an llms.txt file so AI crawlers can discover your content structure without heavy crawling. Generate llms.txt →
  • Run a full entropy audit to find which DOM regions waste the most tokens. Run Entropy Audit →
🧪

JavaScript Rendering Check

We check what AI crawlers miss when they skip JavaScript execution.

Running headless browser to simulate AI extraction…
🛡️

Traditional SEO

47/100 25 % of Global Score 🟢 High Confidence

📝 Title Tag

7 chars
Too short

Optimal range: 30–60 characters for SERP display.

📋 Meta Description

107 chars
Too short

Optimal range: 120–160 characters for snippet control.

🔤 Heading Hierarchy

  • ✓ Exactly 1 <h1> tag — found 1
  • ✓ Has <h2> headings — found 6
  • ✓ <h2> not before <h1>

🔍 Indexability

  • ✓ Canonical tag present → https://pytorch.org/
  • ✓ No noindex directive
  • ✓ Meta viewport set
  • ✓ HTML lang attribute → en-US
  • ➖ Hreflang tags — N/A (single language site)
  • ✓ Googlebot allowed by robots.txt

🌐 Social / OpenGraph

  • ✓ og:title — PyTorch
  • ✓ og:description — PyTorch Foundation is the deep learning community home for the open source PyTorch framework and ecosystem.
  • ✓ og:image — preview
  • ✗ twitter:card
📐 How the SEO Pillar score is calculated

SEO Pillar = Title (20 pts) + Meta Desc (20 pts) + Heading Hierarchy (20 pts) + Indexability (20 pts) + Social/OG (20 pts)

Each sub-score is derived from the checks above. Canonical tag, lang attribute, og:image, and a single H1 are the highest-impact items.

🤖

AI Readiness / GEO

72/100 40 % of Global Score 🟢 High Confidence

This pillar aggregates citation share, hallucination risk, bot access, schema health, and content extractability. The individual diagnostic sections below contribute to this score.

🔗

Citation Alternatives

Research
💡
Insight: In the developer sector, hikkoshizamurai.jp (ACRI: 88) currently has stronger AI extractability. AI models tend to prefer sources with higher semantic structure and schema coverage. Domains with ACRI < 40 see 3.5× more hallucinations. Read the research →
pytorch.org
56
Your ACRI Score
88
Industry Peer ACRI
AI models prioritize pages with strong semantic structure and schema coverage. hikkoshizamurai.jp has schema coverage of 5 blocks and uses Custom / Proprietary. Improve your score by implementing the remediation patches below.
📊 Side-by-Side Comparison →
🚨

Hallucination Risk

Research

Is AI lying about your brand? This panel measures how likely LLMs are to hallucinate facts when extracting information from your page.

Analyzing hallucination risk…

🤖 Bot Access Matrix

GPTBot (OpenAI)
Allowed
ClaudeBot (Anthropic)
Allowed
CCBot (Common Crawl)
Allowed
Google-Extended
Allowed
Googlebot
Allowed

👻 Rendering (Ghost Ratio) Docs

Ghost Ratio 0%
0% — Safe 50% 100% — Risk
Status Server-Side Rendered (Safe)
Rendering Type SSR

📊 Structure & Information Density Docs

Structure Grade 60/100 — Good
Structured Elements 100 elements (100 lists, 0 rows, 0 headers)
Total Words935
Raw Density10.7%

🏷️ Schema Health Docs

Organization Schema ❌ Missing
Product / Service Schema ⚠️ Not Found
Total Schema Blocks0 — No JSON-LD detected

Schema Coverage Map

0/7 schema types detected
❌ Organization
❌ Product/Service
❌ Breadcrumb
❌ FAQ
❌ Article
❌ WebSite
💡Organization schema missing. AI models cannot identify your brand entity. Without it, your brand won't appear in Knowledge Panels or be associated with your content.
💡Product / Service schema missing. AI models don't know this is a SaaS product. Add Product or SoftwareApplication schema so AI understands what you offer and can surface pricing/features.
💡BreadcrumbList schema missing. AI cannot understand your site hierarchy or how pages relate to each other.
💡FAQ schema missing. Adding FAQPage schema lets AI models directly extract Q&A pairs for Featured Snippets and chatbot answers.
💡WebSite schema missing. Add WebSite + SearchAction so Google can generate a Sitelinks Search Box for your brand in AI results.

📐 AI Efficiency Metrics Docs

48
AI Extractability
Medium
Crawl Cost
None
Blocklist Risk
Extractability48/100 — AI models can partially extract answers from this page
Crawl CostMedium (50/100) — moderate for AI crawlers to process
Blocklist RiskNone — 0 of 5 AI crawlers blocked

Token Bloat Research

5%
🗑️ 95%
Useful Content (10.3 KB)Bloat (177.8 KB)
Token Bloat Ratio18.2× — Heavy

Multimodal Readiness

Visual Context100% Optimized for Vision
Image Alt Coverage1 / 1 images have alt text

TDM Rights

TDM-Reservation HeaderNot set
X-Robots-Tag: noaiNot set

🔥 Structural Entropy Check Research

0 Entropy
Poor Token Bloat: High
Noise Ratio: 94.5% · SNR: 0.06 · Signal: 2645 / Noise: 45514 tokens

🔬 AI-Crawler Simulation

See your website the way AI crawlers do. CSS stripped, structure labeled, content chunked.

🌐
This is what humans see — styled, branded, visual.
Toggle to "AI Agent View" to see what GPTBot, ClaudeBot, and other AI crawlers actually extract from this page.
🤖

AI Answer Preview

NEW

See how AI models summarize your site. Left: your actual content. Right: what the LLM extracts and says about you.

Simulating AI extraction…
🧠

The LLM Interpretation

AI-VERIFIED

SEODiff AI analyzed the extracted content of pytorch.org and produced this structured business intelligence. Fields marked SEMANTIC VOID indicate information the AI could not find — a critical gap in your site’s machine-readability.

Core Offering
This website showcases PyTorch, a flexible and open-source machine learning framework, and its ecosystem of tools and projects designed to
Target Audience
Machine learning researchers, deep learning engineers, data scientists, and developers working with large language models and AI applications.
Pricing Model
Open-source and free to use. Cloud credits are available through the PyTorch Foundation Cloud Credit Program.
🔗 Integration Partners
vLLMDeepSpeedRayArm
🏆 Competitive Moat
PyTorch’s open-source nature, extensive community support, and continuous innovation in areas like Mamba, DeepSpeed, and hardware acceleration provide a strong competitive advantage.
📊 Content Depth
8/10
🔄 Programmatic SEO Signals
Blog posts frequently cover new releases and updates.Template-generated pages for tutorials and resources.
⚡ Key Pain Points
• Lack of structured FAQ schema
• Thin landing pages for features
Analyzed by SEODiff AI · 2026-03-01

🔧 Tech Stack

FrameworkWordPress
AI-Readiness Score85/100
Servernginx
CDN
HTTP Status200
Load Time540 ms
Raw HTML Size188.1 KB
Visible Text Size10.3 KB

Performance & Speed

59/100 20 % of Global Score 🟢 High Confidence

⏱️ Time to First Byte

540 ms
Acceptable — room for improvement

Google considers <200 ms "good". AI crawlers may have even shorter timeouts.

📦 Page Weight

889
DOM nodes
188 KB
HTML payload
Moderate weight — acceptable for most scenarios

🗄️ Cache & CDN

  • ✓ Cache-Control header → public, max-age=60, s-maxage=43200, stale-while-revalidate=86400, stale-if-error=604800
  • ✗ CDN cache status
  • ✗ CDN detected

🔬 Tracker Tax

0
tracker scripts
0
third-party domains
0.0%
token overhead
Minimal tracker load — clean signal for bots
📐 How the Performance Pillar score is calculated

Perf Pillar = TTFB (35 pts) + Page Weight (25 pts) + Cache/CDN (20 pts) + Tracker Tax (20 pts)

TTFB <200 ms = full marks. DOM >3000 or payload >300 KB incurs heavy penalties. Tracker scripts beyond 5 reduce score.

🏗️

Architecture & Trust

93/100 15 % of Global Score 🟢 High Confidence

🗺️ Sitemap & Robots

  • ✓ Sitemap declared in robots.txt → https://pytorch.org/wp-sitemap.xml
  • ✓ Googlebot allowed
  • ✓ GPTBot allowed
  • ✓ ClaudeBot allowed

🔗 Linking

88
internal links
24
external links
Good internal linking — helps crawlers discover content

🔒 Security & Trust

  • ✓ HSTS header (Strict-Transport-Security)
  • ✗ Content-Security-Policy header
  • ✓ HTTP status 200 OK (got 200)

♿ Accessibility Signals

  • ✓ HTML lang attribute → en-US
  • ✓ Meta viewport for mobile
  • ✓ Single H1 for screen readers
📐 How the Architecture Pillar score is calculated

Arch Pillar = Sitemap & Robots (30 pts) + Linking (25 pts) + Security (25 pts) + Accessibility (20 pts)

Having a valid sitemap, allowing AI bots, HSTS, and a good internal link count are the highest-impact items.

🏅 AI-Verified Trust Badge

Your site scores 56/100. Reach 80+ to unlock the green "AI-Verified" badge. Fix the issues below to improve your score.

AI-Verified badge for pytorch.org
Pending Audit — score below 80 threshold
<a href="https://seodiff.io/radar/domains/pytorch.org" rel="noopener"><img src="https://seodiff.io/api/v1/badge?domain=pytorch.org" alt="AI-Verified by SEODiff" width="280" height="52"></a>

💡 Paste in your site footer, GitHub README, or email signature. Badge updates automatically as your score changes.

� Deep Crawl Analysis 139 pages · Deep-10

Homepage ACRI
56
Single-page score
0
Consistent readability
Δ delta
Site-Wide ACRI
56
Avg across 139 pages · Range 0–77
Topical Cohesion
8%
Topical Drift
TF-IDF cosine similarity
Total Words
250665
Avg Bloat
22.7×
RAG Fractures [?]
7
⚠️
7 RAG-Chunking Fractures Detected

Poorly formatted tables or pricing grids on 7 pages will be split incorrectly during RAG chunking, causing AI models to hallucinate prices and features.

Page Type ACRI Token Bloat Words Status
https://pytorch.org/blog/how-computational-graphs-are-executed-in-pytorch/
How Computational Graphs are Executed in PyTorch – PyTorch
blog 77 7.5× 6251
https://pytorch.org/blog/int4-decoding/
INT4 Decoding GQA CUDA Optimizations for LLM Inference – PyTorch
pricing 77 7.7× 6185 ⚠️ RAG Fracture
https://pytorch.org/blog/ambient-clinical-intelligence-generating-medical-reports-with-pytorch/
Ambient Clinical Intelligence: Generating Medical Reports with PyTorch – PyTorch
pricing 74 9.8× 3903 💰 Pricing
https://pytorch.org/blog/efficient-large-scale-training-with-pytorch/
Efficient Large-Scale Training with Pytorch FSDP and AWS – PyTorch
pricing 74 9.1× 4363 ⚠️ RAG Fracture
https://pytorch.org/blog/pytorch-1-12-new-library-releases/
New library updates in PyTorch 1.12 – PyTorch
pricing 67 12.5× 3250 💰 Pricing
https://pytorch.org/blog/scaling-multimodal-foundation-models-in-torchmultimodal-with-pytorch-distributed/
Scaling Multimodal Foundation Models in TorchMultimodal with Pytorch Distributed – PyTorch
pricing 64 14.8× 2488 💰 Pricing
https://pytorch.org/blog/straggler-mitigation/
Straggler Mitigation On PyTorch DDP By Hierarchical SGD – PyTorch
pricing 64 12.0× 3119 💰 Pricing
https://pytorch.org/blog/quantization-in-practice/
Practical Quantization in PyTorch – PyTorch
blog 64 12.6× 3093
https://pytorch.org/blog/hopper-tma-unit/
Deep Dive on the Hopper TMA Unit for FP8 GEMMs – PyTorch
pricing 64 13.9× 2655 💰 Pricing
https://pytorch.org/blog/quantization-aware-training/
Quantization-Aware Training for Large Language Models with PyTorch – PyTorch
pricing 64 12.7× 2986 💰 Pricing
https://pytorch.org/blog/accelerated-pytorch-inference/
Accelerated PyTorch inference with torch.compile on AWS Graviton processors – PyTorch
blog 64 10.7× 3590
https://pytorch.org/blog/accelerating-generative-ai-4/
Accelerating Generative AI with PyTorch IV: Seamless M4T, fast – PyTorch
pricing 64 14.0× 2697 💰 Pricing
https://pytorch.org/blog/amazon-sagemaker-w-torchserve/
Accelerate AI models on GPU using Amazon SageMaker multi-model endpoints with TorchServe, saving up to 75% on inference costs – PyTorch
pricing 64 12.8× 2991 💰 Pricing
https://pytorch.org/blog/accelerating-generative-ai-2/
Accelerating Generative AI with PyTorch II: GPT, Fast – PyTorch
pricing 64 11.5× 3380 💰 Pricing
https://pytorch.org/blog/accelerating-generative-ai/
Accelerating Generative AI with PyTorch: Segment Anything, Fast – PyTorch
blog 64 13.7× 2856
https://pytorch.org/blog/high-performance-llama-2/
High-Performance Llama 2 Training and Inference with PyTorch/XLA on Cloud TPUs – PyTorch
pricing 64 10.6× 3754 ⚠️ RAG Fracture
https://pytorch.org/blog/high-performance-llama/
High performance Llama 2 deployments with AWS Inferentia2 using TorchServe – PyTorch
pricing 64 13.5× 2748 💰 Pricing
https://pytorch.org/blog/inside-the-matrix/
Inside the Matrix: Visualizing Matrix Multiplication, Attention and Beyond – PyTorch
pricing 64 14.2× 5441 💰 Pricing
https://pytorch.org/blog/pytorch-2-0-release/
PyTorch 2.0: Our next generation release that is faster, more Pythonic and Dynamic as ever – PyTorch
pricing 64 11.6× 3229 ⚠️ RAG Fracture
https://pytorch.org/blog/new-library-updates-in-pytorch-1-13/
New Library Updates in PyTorch 1.13 – PyTorch
pricing 64 13.4× 2763 💰 Pricing
Showing 20 of 100 pages. Unlock full subpage table →
📂
Health by Sub-Directory
Average ACRI and top issues aggregated by URL path prefix
Path Pages Avg ACRI Ghost % Bloat Top Issue
/blog/ 130 59 0% 23.1× High JS Bloat
/products/ 1 0 0% 0.0× Low AI Readiness
/faq/ 1 0 0% 0.0× Low AI Readiness
/case-studies/ 1 53 1% 35.7× Bot Blocked
/docs/ 1 47 0% 5.5× High JS Bloat
/pricing/ 1 0 0% 0.0× Low AI Readiness
/about/ 1 0 0% 0.0× Low AI Readiness
/integrations/ 1 0 0% 0.0× Low AI Readiness
/features/ 1 53 1% 41.0× Bot Blocked
/contact/ 1 46 0% 59.6× High JS Bloat
🔄 Re-Crawl & Update 📡 Track this Domain

Scores update automatically each month. Create a free account for on-demand re-crawls (3/month free).

🔌 API Access

Pull this data programmatically. All sub-page metrics are available via our public API.

curl https://seodiff.io/api/v1/deep10/domain/pytorch.org

Get your free API key — 100 requests/month included.

🔗 Similar developer Sites

Domains with a similar tech stack, industry, and AI readiness profile to pytorch.org. Compare side-by-side.

Domain ACRI AI Score Tech Stack Token Bloat Schema
pytorch.org (this site) 56 76 WordPress 18.2× 0
nationalsalonsupplies.com.au 80 90 WordPress 17.1× 3 Compare →
coveti.com 80 88 WordPress 9.6× 2 Compare →
aronia-charlottenburg.ro 80 90 WordPress 7.6× 1 Compare →
askbart.org 81 84 WordPress 2.6× 1 Compare →
esmile-24.com 81 84 WordPress 2.2× 1 Compare →
Compare All 5 Similar Sites →

📊 Semantic Share of Voice

How often would an AI cite pytorch.org when users ask about topics in this domain's niche? We run entity queries through our 188k-page search index and measure citation probability.

Analyzing citation landscape…

🎭

Bait & Switch Delta

A 5 PAGES

Compares your homepage rendering quality with inner pages. A high drift score means AI crawlers see a polished homepage but degraded inner content — the "bait & switch" that erodes trust.

53
Homepage ACRI
51
Inner Avg ACRI
+2
ACRI Delta
60%
Homepage Ghost
30%
Inner Avg Ghost
1
Drift Score [?]
Worst Inner Pages
53 60% pricing https://pytorch.org/case-studies
46 40% support https://pytorch.org/contact
59 20% blog https://pytorch.org/blog
🛡️

E-E-A-T Trust Signals

F 15/100

Trust indicators extracted from surface pages. These signals help AI systems verify your site's Experience, Expertise, Authoritativeness, and Trustworthiness.

Physical Address
Phone Number
Email Contact
About Page
Contact Page
Privacy Policy
Terms of Service
Named Leadership
🔗

Citation Profile

17 DOMAINS

Outbound citation patterns across surface-crawled pages. Sites that cite diverse, authoritative sources signal higher E-E-A-T to AI systems.

53
Total Links
17
Unique Domains
10.6
Avg/Page
32%
Diversity
docs.pytorch.org facebook.com discuss.pytorch.org youtube.com landscape.pytorch.org events.linuxfoundation.org linkedin.com discord.com github.com join.slack.com
🏘️ Outbound Neighborhood Trust Avg Trust: 33.5

AI trust scores for the domains pytorch.org links to. Citing high-trust sources lifts your own credibility signal.

🩹

Remediation Patches

COPY-PASTE

Auto-generated code fixes tailored to pytorch.org. Copy and paste these into your codebase to improve AI visibility. These patches are mathematically proven to increase extraction accuracy →

Add Organization JSON-LD
High Impact ⏱ 5 min
AI models cannot identify your brand entity without Organization schema. This is the #1 fix for AI visibility.
html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Pytorch",
  "url": "https://pytorch.org",
  "logo": "https://pytorch.org/wp-content/uploads/2024/10/cropped-favicon-32x32.webp",
  "sameAs": []
}
</script>
Add WebSite + SearchAction JSON-LD
High Impact ⏱ 5 min
Enables the Sitelinks Search Box in Google and allows AI to understand your site structure.
html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "WebSite",
  "name": "Pytorch",
  "url": "https://pytorch.org",
  "potentialAction": {
    "@type": "SearchAction",
    "target": "https://pytorch.org/search?q={search_term_string}",
    "query-input": "required name=search_term_string"
  }
}
</script>
Reduce Token Bloat
Medium Impact ⏱ 1–2 hrs
Only 5% of your HTML is useful content. AI crawlers waste context window tokens on bloat.
html
<!-- Move inline CSS to external stylesheets -->
<link rel="stylesheet" href="/css/main.css">

<!-- Move inline scripts to external files with defer -->
<script src="/js/app.js" defer></script>

<!-- Remove duplicate navigation blocks -->
<!-- Keep only ONE <nav> in the <header> -->

<!-- Ensure <main> wraps your primary content -->
<main>
  <!-- Your content here — this is what AI sees first -->
</main>
Add FAQ Schema
Medium Impact ⏱ 10 min
FAQ schema lets AI models directly extract Q&A pairs. This is the easiest way to get featured in AI responses.
html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What is Pytorch?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Add your answer here — describe what Pytorch does in 1-2 sentences."
      }
    },
    {
      "@type": "Question",
      "name": "How does Pytorch work?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Explain the key features and how users interact with Pytorch."
      }
    }
  ]
}
</script>
📈

Projected Impact

ROI EST.

If you apply the patches above, here's the estimated improvement for pytorch.org:

Current Score
76
Projected Score
94
Improvement
+18 pts
Add Organization schema +6 pts
Add WebSite schema +4 pts
Reduce token bloat +5 pts
Add FAQ schema +3 pts

*Estimates based on SEODiff's scoring model. Actual results depend on implementation quality.

📋 Data Export

Download scores and metadata for audits, client reports, or CI/CD pipelines. Exports contain computed metrics only (no copyrighted content).

All data is generated automatically and updated with each crawl. JSON exports contain scores and metadata only (no copyrighted content).

Is this your company?

Monitor your AI visibility score weekly and get alerted when changes happen.

Start Free →

🧭 Self-Diffing (Private Layer)

For owned domains, combine this world snapshot with private drift + regression history.
Template Drift
Track in My Site
Drift → Traffic Impact
In development coming soon
Regression Incidents
Track in My Site
Internal Linking
Deep Audit graph
Semantic Structure
GEO view in Deep Audit
Content Quality
Thin/duplicate tracking

🕒 History

Score over timeAvailable in My Site history
Drift eventsTemplate timeline + incidents
Drift → Revenue AttributionComing soon
Schema/rendering/extractability changesTracked per scan in project history
🔍 Found indexing issues?
Run a free deep audit to diagnose crawled-not-indexed, soft 404s, redirect errors, and more.
Free Deep Audit → GSC Error Guide →