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Market/Categories/Developer & AI Platform/Facebook’s PyTorch

Independent product intelligence · Worldwide · 2026-05-01 → 2026-07-31

Facebook’s PyTorchpytorch.org

No product description has been published for this domain yet. Everything below is measured directly.

Developer & AI Platformpytorch.orgTracked since 2026-08-192 discovery sources
1.7MBacklinks
28.4KReferring domains
50Domain authority
+2.5%Referring domains · 90 days

Authority & distribution

How strong is Facebook’s PyTorch’s web footprint?

Backlinks measure accumulated distribution; referring domains show how broadly that authority is spread. Both are observable on the open web, so both are published for every product here.

Backlinks

1.7MCurrent snapshot

Referring domains

28.4KCurrent snapshot

Authority

50Domain authority · category median 22

90-day move

+2.5%Referring domains, last 90 days
At 50, Facebook’s PyTorch sits above the 22 median for its category.

Trajectory · Pro

The counts above are the latest of 370 daily observations. The curve through them is on the full profile.

See the trajectoryOpen the full profile

Traffic & engagement

Where Facebook’s PyTorch ranks

Measured · Pro

Measured for this product: global rank, country rank and category rank.

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AI referral visibility

Which AI assistants are already sending Facebook’s PyTorch traffic?

Measured · Pro

Measured for this product: AI referral traffic, which assistants refer it and which pages those referrals land on.

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Product profile

What Facebook’s PyTorch is selling.

Traffic makes more sense when you can connect it to the actual product promise.

“Facebook’s PyTorch”

No usable description reached this profile from any discovery source, so none is shown. The measured signals below are unaffected.

Developer & AI PlatformSeen 2026-08-19 → 2026-08-21Coverage tier C

What we have measured

4 of 8 signal groups are available for this product: identity, authority and backlinks, AI referrals, search demand.

Not measured for this domain: traffic and engagement, audience demographics, country distribution, acquisition mix. Those sections are left out of the page rather than filled with estimates.

Canonical website: https://pytorch.org

Observed across 2 discovery sources.

Research questions

What the evidence answers about Facebook’s PyTorch.

Every answer is tied to a source we collected, and the questions with no evidence behind them are left unanswered rather than guessed.

What is PyTorch and what problem does it solve?

PyTorch is an open-source deep learning framework that simplifies AI model development and training. It is a foundational tool for building, testing, and deploying AI models, enabling developers to move from research to production seamlessly.

What is PyTorch used for and in what situations?

PyTorch is used for building and training AI models in both research and production environments. It is employed for tasks in computer vision, natural language processing (NLP), and more, with support for distributed training on AMD GPUs and on-device agentic AI workflows.

Who is PyTorch for?

PyTorch is for AI developers, researchers, and engineers who need a flexible and production-ready framework for building, training, and deploying deep learning models. It is used by the open-source community and organizations like Meta.

What key features and capabilities does PyTorch offer?

PyTorch offers production readiness with TorchScript and TorchServe, distributed training via torch.distributed, a robust ecosystem for computer vision and NLP, and broad cloud platform support for scaling. It also allows installing locally or launching instantly on supported cloud platforms.

4 of 6 research questions are answered for this product. The rest need source evidence we have not collected yet, so they are left unanswered rather than guessed.

Behind the lock

Unlock full Facebook’s PyTorch intelligence.

  • Backlink trajectoryThe figures above are the latest observation. The daily curve behind them holds 370.
  • AI referral detailHow much traffic assistants send, which 9 of them do it, and the 24 pages they land on.
  • Search structure and ranking depthOrganic against paid, brand against non-brand, and how many keywords rank in the top three against the long tail — which is what decides whether the demand is portable or tied to the name.
  • The rest of the marketPage through every leaderboard 100 rows at a time, put any five products side by side, and query the whole dataset over API / MCP.

Worldwide estimates · Data period 2026-05-01 → 2026-07-31. Figures are measured estimates intended for market research. Signals we have not measured for this domain are omitted, never estimated; a measured zero is still reported as zero. How this was measured