PyTorch website screenshot

PyTorch

APIs and resources for PyTorch, an open source machine learning framework for tensor computation and deep learning developed by Meta.

PyTorch publishes 5 APIs on the APIs.io network. Tagged areas include Artificial Intelligence, Deep Learning, Machine-Learning, Neural Networks, and Open-Source.

PyTorch’s developer surface includes engineering blog, getting-started guide, and 7 more developer resources.

13.4/100 emerging ▬ flat Agent 3/100 human only Full breakdown ↓
scored 2026-08-25 · rubric v0.14.0
AccessFreemium
5 APIs
Artificial IntelligenceDeep LearningMachine-LearningNeural NetworksOpen-SourcePython

Kin Score

Kin Score Kin Score How this is scored →
scored 2026-08-25 · rubric v0.14.0
Composite quality — 13.4/100 · emerging
Contract Quality 0.0 / 25
Developer Ergonomics 3.3 / 20
Access Clarity 3.2 / 20
Operational Transparency 1.4 / 13
Contract Governance 0.0 / 12
Discoverability 5.6 / 10
Agent readiness — 3/100 · human only
Machine-Readable Contract 0 / 18
Agentic Access Contract 0 / 10
Documented Reversibility 0 / 6
MCP Server 0 / 12
Machine-Readable Auth 0 / 10
Idempotency 0 / 9
Stable Error Semantics 0 / 8
Request/Response Examples 0 / 7
Rate-Limit Signaling 7 / 7
Typed Event Surface 0 / 6
Agent Skills 0 / 5
Well-Known Catalog 0 / 4
Consent & Bot Identity 0 / 3
A2A Agent Card 0 / 8
Dry-Run / Simulate Mode 0 / 4
Delegated User Identity 0 / 6
Protected Resource Metadata 0 / 5
Registration Without a Human 0 / 6
Agentic Commerce Surface 0 / 5
Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. This rating is computed from github.com/api-evangelist/pytorch: open an issue to ask a question, or submit a pull request to add artifacts. Want it done for you? Prioritized profiling — $2,500 →

APIs 5

Individual APIs this provider publishes, each with its own machine-readable definition.

PyTorch Core API

Core PyTorch library for tensor computation and deep learning.

TorchVision API

Computer vision library for PyTorch with datasets, models, and transforms.

TorchText API

Natural language processing library for PyTorch.

TorchAudio API

Audio processing library for PyTorch.

PyTorch Hub API

Pre-trained model repository and discovery API.

Pricing Plans 1

Published pricing tiers and plan structures.

Pytorch Plans Pricing

3 plans

PLANS

Rate Limits 1

Documented rate limits and quota policies.

Pytorch Rate Limits

5 limits

RATE LIMITS

FinOps 1

Cost, billing, and metering signals for API financial operations.

Security Posture 1

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Pytorch Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Resources

Get Started 1

Portal, sign-up, and the first successful call

Build 1

SDKs, sample code, and the tooling you integrate with

Access & Security 1

Authentication, authorization, and security posture

Operate 2

Status, limits, changes, and where to get help

Company 3

The organization behind the API

Other 1

Properties that don't map to a standard resource type

Source (apis.yml)

apis.yml Raw ↑
aid: pytorch
name: PyTorch
description: APIs and resources for PyTorch, an open source machine learning framework for tensor computation and deep learning
  developed by Meta.
type: Index
accessModel:
  pricing: freemium
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Freemium
  confidence: medium
  source:
  - plans
  generated: '2026-07-22'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/pytorch.png
tags:
- Artificial Intelligence
- Deep Learning
- Machine-Learning
- Neural Networks
- Open-Source
- Python
tags_raw:
- Artificial Intelligence
- Deep Learning
- Machine Learning
- Neural Networks
- Open Source
- Python
url: https://raw.githubusercontent.com/api-evangelist/pytorch/refs/heads/main/apis.yml
created: '2024-01-01'
modified: '2026-04-28'
specificationVersion: '0.23'
apis:
- aid: pytorch:pytorch-core-api
  name: PyTorch Core API
  description: Core PyTorch library for tensor computation and deep learning.
  humanURL: https://pytorch.org/docs/stable/index.html
  tags:
  - Deep Learning
  - Machine-Learning
  - Tensors
  tags_raw:
  - Deep Learning
  - Machine Learning
  - Tensors
  properties:
  - type: Documentation
    url: https://pytorch.org/docs/stable/index.html
  - type: GettingStarted
    url: https://pytorch.org/get-started/locally/
  - type: APIReference
    url: https://pytorch.org/docs/stable/torch.html
  - type: GitHub
    url: https://github.com/pytorch/pytorch
- aid: pytorch:torchvision
  name: TorchVision API
  description: Computer vision library for PyTorch with datasets, models, and transforms.
  humanURL: https://pytorch.org/vision/stable/index.html
  tags:
  - Computer-Vision
  - Image Processing
  - Models
  tags_raw:
  - Computer Vision
  - Image Processing
  - Models
  properties:
  - type: Documentation
    url: https://pytorch.org/vision/stable/index.html
  - type: GitHub
    url: https://github.com/pytorch/vision
  - type: Models
    url: https://pytorch.org/vision/stable/models.html
- aid: pytorch:torchtext
  name: TorchText API
  description: Natural language processing library for PyTorch.
  humanURL: https://pytorch.org/text/stable/index.html
  tags:
  - NLP
  - Text Processing
  properties:
  - type: Documentation
    url: https://pytorch.org/text/stable/index.html
  - type: GitHub
    url: https://github.com/pytorch/text
- aid: pytorch:torchaudio
  name: TorchAudio API
  description: Audio processing library for PyTorch.
  humanURL: https://pytorch.org/audio/stable/index.html
  tags:
  - Audio
  - Speech Recognition
  properties:
  - type: Documentation
    url: https://pytorch.org/audio/stable/index.html
  - type: GitHub
    url: https://github.com/pytorch/audio
  - type: Tutorials
    url: https://pytorch.org/audio/stable/tutorials.html
- aid: pytorch:pytorch-hub
  name: PyTorch Hub API
  description: Pre-trained model repository and discovery API.
  humanURL: https://pytorch.org/hub/
  tags:
  - Pre-Trained Models
  - Model Hub
  - Transfer Learning
  properties:
  - type: Documentation
    url: https://pytorch.org/docs/stable/hub.html
  - type: Models
    url: https://pytorch.org/hub/research-models
common:
- type: DomainSecurity
  url: security/pytorch-domain-security.yml
- type: LinkedIn
  url: https://www.linkedin.com/company/pytorch
- type: Blog
  url: https://pytorch.org/blog/
- type: Community
  url: https://pytorch.org/community
- type: Forums
  url: https://discuss.pytorch.org/
- type: GitHubOrganization
  url: https://github.com/pytorch
- type: GettingStarted
  url: https://pytorch.org/get-started/pytorch-2.0/
- type: Website
  url: https://pytorch.org
- type: Ecosystem
  url: https://pytorch.org/ecosystem
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com

Work with this as data

Every provider here is available over the APIs.io API and to AI agents over MCP.

MCP server

One button, every client — Claude, Cursor, VS Code and the rest.

https://apis.io/mcp

Tools for providers

9 MCP tools reach this
  • find_providersBrowse and filter every provider in the catalog.
  • get_provider_artifactsEvery artifact this provider publishes, grouped by type.
  • get_provider_operationsEvery operation across all of their OpenAPIs — one call instead of parsing every spec.
  • get_provider_toolsEvery MCP tool they ship, with the operation each wraps.
  • get_provider_evidenceHow each part of their score was established. Free — the basis for a claim should not sit behind it.
  • get_provider_ratingPRO — composite, band, trend and facet scores.
  • apis_io_searchSTART HERE — APIs, providers and tags for one query, each with its total.
  • resolveTurn a domain, URL or GitHub org into the provider it belongs to.
  • find_cohortsEvery scored population of providers in the catalog.
All 92 tools

Call it yourself

curl for this page
This provider
curl "https://apis.io/api/v1/providers/pytorch"
All providers
curl "https://apis.io/api/v1/providers?limit=25"
Every operation they expose
curl "https://apis.io/api/v1/providers/pytorch/operations?limit=25"
How their score was established
curl "https://apis.io/api/v1/providers/pytorch/evidence"

Discovery needs no key. Ratings and market analysis are Pro.

Get an API key

Free tier, no email required.

A second provider on the same verified email joins the account you already have.