Google TensorFlow website screenshot

Google TensorFlow

Google TensorFlow is an open-source machine learning framework providing APIs and tools for building, training, and deploying ML models, including TensorFlow Serving for model inference and TensorFlow Hub for reusable model components.

Google TensorFlow publishes 2 APIs on the APIs.io network: Model Status API and Prediction API. Tagged areas include Artificial Intelligence, Deep Learning, Google, Machine-Learning, and Model Serving.

The Google TensorFlow catalog on APIs.io includes 1 JSON-LD context and 1 Spectral governance ruleset.

Google TensorFlow’s developer surface includes getting-started guide, pricing, support, engineering blog, and 7 more developer resources.

34.5/100 thin ▬ flat Agent 17/100 agent aware saas Full breakdown ↓
scored 2026-09-08 · rubric v0.20.0
AccessFree
1 APIs
Artificial IntelligenceDeep LearningGoogleMachine-LearningModel ServingOpen-Source

Kin Score

Kin Score Kin Score How this is scored →
scored 2026-09-08 · rubric v0.20.0
Create-or-Update Ergonomics applies to this provider. This API accepts writes, so it carries 10 points of the composite. It is scored from the published contracts themselves: whether a caller can create-or-update in one call, whether the write accepts a key the caller already holds, and whether the response says which branch ran. Without that, every write needs a search-and-branch in front of it, and the first time that check is skipped a duplicate record is created. Scored against the observed mean rather than raw — a provider at the catalog average is unchanged by this facet, not penalised by it.
Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. Every facet and dimension name above is a link: it opens that measurement's own page — what it means, the exact checks that feed it, how the whole catalog distributes on it, and the providers at the top of it. This rating is computed from github.com/api-evangelist/google-tensorflow: open an issue to ask a question, or submit a pull request to add artifacts. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

APIs 4

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

TensorFlow Hub API

TensorFlow Hub provides a repository of reusable trained machine learning models. The API allows developers to search, discover, and download pre-trained models and model compon...

TensorFlow Model Analysis API

TensorFlow Model Analysis (TFMA) provides tools and APIs for evaluating TensorFlow models. It enables computing metrics over large datasets using Apache Beam, slicing evaluation...

Google TensorFlow Model Status API

Model metadata and status operations

Google TensorFlow Prediction API

Model inference operations

Open Collections 4

Open, tool-agnostic API collections (OpenAPI-derived and Bruno).

API Collection

OPEN COLLECTION

Pricing Plans 1

Published pricing tiers and plan structures.

Rate Limits 1

Documented rate limits and quota policies.

Google Tensorflow Rate Limits

2 limits

RATE LIMITS

FinOps 1

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

Semantic Vocabularies 1

JSON-LD contexts and semantic vocabularies used across these APIs.

Google Tensorflow Context

0 classes · 4 properties

JSON-LD

Spectral Rules 1

Spectral governance rulesets for linting and validating these APIs.

Google TensorFlow API Rules

4 rules · 3 warnings 1 info

SPECTRAL

JSON Schema 1

Standalone JSON Schema definitions for this provider's data models.

TensorFlow Serving Predict Request

3 properties

JSON SCHEMA

Security Posture 1

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

Google Tensorflow Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Agentic Access 1

Recommended x-agentic-access execution contracts for AI agents.

Google Tensorflow Agentic Access

5 operations · 3 acting

5 operations · 3 acting

AGENTIC

Resources

Get Started 1

Portal, sign-up, and the first successful call

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

Design & Contract 1

Pagination, idempotency, versioning, errors, and events

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

Commercial 1

Pricing, plans, and the legal terms of use

Company 3

The organization behind the API

Source (apis.yml)

apis.yml Raw ↑
aid: google-tensorflow
name: Google TensorFlow
description: Google TensorFlow is an open-source machine learning framework providing APIs and tools for building, training,
  and deploying ML models, including TensorFlow Serving for model inference and TensorFlow Hub for reusable model components.
deliveryModel:
  model: saas
  open_source: false
  commercial: true
  callable_host: false
  label: Hosted service · you call their endpoint
  confidence: medium
  source:
  - openapi
  - pricing
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: free
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Free
  confidence: medium
  source:
  - plans
  generated: '2026-07-22'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/google-tensorflow.png
url: https://raw.githubusercontent.com/api-evangelist/google-tensorflow/refs/heads/main/apis.yml
created: '2026-03-13'
modified: '2026-05-19'
specificationVersion: '0.23'
type: Index
tags:
- Artificial Intelligence
- Deep Learning
- Google
- Machine-Learning
- Model Serving
- Open-Source
tags_raw:
- AI
- Deep Learning
- Google
- Machine Learning
- Model Serving
- Open Source
apis:
- name: TensorFlow Hub API
  description: TensorFlow Hub provides a repository of reusable trained machine learning models. The API allows developers
    to search, discover, and download pre-trained models and model components (SavedModels, TF.js models, TFLite models) that
    can be reused for transfer learning and inference in new applications.
  image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/apis-json-logo.jpg
  humanURL: https://tfhub.dev
  baseURL: https://tfhub.dev
  tags:
  - Models
  - Pre-Trained Models
  - Transfer Learning
  properties:
  - type: Documentation
    url: https://www.tensorflow.org/hub
- name: TensorFlow Model Analysis API
  description: TensorFlow Model Analysis (TFMA) provides tools and APIs for evaluating TensorFlow models. It enables computing
    metrics over large datasets using Apache Beam, slicing evaluation results across different features, and tracking model
    performance over time for validation and monitoring purposes.
  image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/apis-json-logo.jpg
  humanURL: https://www.tensorflow.org/tfx/model_analysis/get_started
  baseURL: https://localhost
  tags:
  - Analysis
  - Metrics
  - Model Evaluation
  properties:
  - type: Documentation
    url: https://www.tensorflow.org/tfx/model_analysis/get_started
- aid: google-tensorflow:google-tensorflow-model-status-api
  name: Google TensorFlow Model Status API
  description: Model metadata and status operations
  humanURL: https://www.tensorflow.org/tfx/serving/api_rest
  baseURL: http://localhost:8501
  tags:
  - Model Status
  properties:
  - type: OpenAPI
    url: openapi/google-tensorflow-model-status-api-openapi.yml
  - type: Documentation
    url: https://www.tensorflow.org/tfx/serving/api_rest
  - type: JSONSchema
    url: json-schema/google-tensorflow-predict-request-schema.json
- aid: google-tensorflow:google-tensorflow-prediction-api
  name: Google TensorFlow Prediction API
  description: Model inference operations
  humanURL: https://www.tensorflow.org/tfx/serving/api_rest
  baseURL: http://localhost:8501
  tags:
  - Prediction
  properties:
  - type: OpenAPI
    url: openapi/google-tensorflow-prediction-api-openapi.yml
  - type: Documentation
    url: https://www.tensorflow.org/tfx/serving/api_rest
  - type: JSONSchema
    url: json-schema/google-tensorflow-predict-request-schema.json
common:
- type: Website
  url: https://www.tensorflow.org/
- type: AgenticAccess
  url: agentic-access/google-tensorflow-agentic-access.yml
- type: DomainSecurity
  url: security/google-tensorflow-domain-security.yml
- type: LinkedIn
  url: https://www.linkedin.com/showcase/tensorflowdev
- type: GettingStarted
  url: https://www.tensorflow.org/learn
- type: Pricing
  url: https://www.tensorflow.org
- type: SDKs
  url: https://www.tensorflow.org/install
- type: Support
  url: https://www.tensorflow.org/community
- type: StatusPage
  url: https://github.com/tensorflow/tensorflow
- type: JSONLD
  url: json-ld/google-tensorflow-context.jsonld
- url: https://blog.tensorflow.org/feeds/posts/default?alt=rss
  type: Blog
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com

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