Pruna AI

Pruna AI builds Performance Models (P-Series) — optimized image and video generation models engineered to be faster, cheaper, and smaller than standard alternatives while keeping quality high. It ships three ways: a hosted HTTP API (P-API) that exposes ~20 models (text-to-image, image editing, upscaling, virtual try-on, text/image-to-video, avatar, animation and replacement, plus LoRA trainers) behind a single endpoint selected via a request header; an open-source Python optimization framework (pruna / pruna-pro) for caching, quantization, pruning, distillation and compilation of your own models; and hosted demos. The P-API uses apikey-header auth with an async submit/poll/download workflow and an optional synchronous mode. Pruna AI is a portfolio company of EQT Ventures.

Pruna AI publishes 3 APIs on the APIs.io network: Content Delivery API, File Management API, and Predictions API. Tagged areas include Company, Artificial Intelligence, Machine-Learning, Image-Generation, and Video Generation.

Pruna AI’s developer surface includes documentation, API reference, getting-started guide, signup flow, pricing, engineering blog, support, and 21 more developer resources.

🌐 Visit website 📡 Source on GitHub

46.1/100 developing ▬ flat Agent 36/100 agent ready saas Full breakdown ↓
scored 2026-09-08 · rubric v0.20.0

1 APIs

Company Artificial Intelligence Machine-Learning Image-Generation Video Generation Generative AI Model Optimization Inference Developer Tools

Kin Score

Kin Score How this is scored →
scored 2026-09-08 · rubric v0.20.0

Composite quality — 46.1/100 · developing

Contract Quality 13.2 / 23

Developer Ergonomics 13.2 / 18

Access Clarity 5.7 / 18

Operational Transparency 2.8 / 12

Contract Governance 0.5 / 11

Discoverability 6.8 / 9

Create-or-Update Ergonomics 0.0 / 10

Agent readiness — 36/100 · agent ready

Machine-Readable Contract 18 / 18

Agentic Access Contract 10 / 10

Documented Reversibility 6 / 6

MCP Server 0 / 12

Machine-Readable Auth 10 / 10

Idempotency 0 / 9

Stable Error Semantics 8 / 8

Request/Response Examples 7 / 7

Rate-Limit Signaling 7 / 7

Typed Event Surface 0 / 6

Agent Skills 5 / 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 Well-Known Document 0 / 5

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/pruna-ai: 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 3

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

Pruna AI Content Delivery API

Download generated content files

Pruna AI File Management API

Upload files to be used as input for predictions

Pruna AI Predictions API

Core prediction workflow operations

Open Collections 4

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

API Collection

OPEN COLLECTION

P Content Delivery API

OPEN COLLECTION

P Content Delivery File Management API

OPEN COLLECTION

P Content Delivery Predictions API

OPEN COLLECTION

Rate Limits 1

Documented rate limits and quota policies.

Pruna Ai Rate Limits

1 limits

RATE LIMITS

Security Posture 2

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

Pruna Ai Authentication

apiKey · 1 scheme

SECURITY

Pruna Ai Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Agentic Access 1

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

Pruna Ai Agentic Access

4 operations · 2 acting

AGENTIC

Resources

Get Started 4

Portal, sign-up, and the first successful call

DeveloperPortal

GettingStarted

SignUp

Sandbox

Documentation 2

Reference material describing how the API behaves

Documentation

Documentation

APIReference

APIReference

Agent Surfaces 4

MCP servers, agent skills, and machine-readable catalogs

X-MCPServerCandidate

LLMsTxt

AgentSkill

AgenticAccess

Design & Contract 5

Pagination, idempotency, versioning, errors, and events

Conventions

ErrorCatalog

Lifecycle

Conformance

DataModel

Build 3

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

GitHubOrganization

Packages

Packages

SDKs

SDKs

Access & Security 2

Authentication, authorization, and security posture

Authentication

Authentication

DomainSecurity

DomainSecurity

Operate 2

Status, limits, changes, and where to get help

Support

Support

RateLimits

RateLimits

Commercial 3

Pricing, plans, and the legal terms of use

Pricing

Pricing

TermsOfService

TermsOfService

PrivacyPolicy

PrivacyPolicy

Company 2

The organization behind the API

Blog

Blog

Website

Website

Other 1

Properties that don't map to a standard resource type

Overlay

Overlay

Source (apis.yml)

aid: pruna-ai
name: Pruna AI
description: 'Pruna AI builds Performance Models (P-Series) — optimized image and video generation models engineered to be
  faster, cheaper, and smaller than standard alternatives while keeping quality high. It ships three ways: a hosted HTTP API
  (P-API) that exposes ~20 models (text-to-image, image editing, upscaling, virtual try-on, text/image-to-video, avatar, animation
  and replacement, plus LoRA trainers) behind a single endpoint selected via a request header; an open-source Python optimization
  framework (pruna / pruna-pro) for caching, quantization, pruning, distillation and compilation of your own models; and hosted
  demos. The P-API uses apikey-header auth with an async submit/poll/download workflow and an optional synchronous mode. Pruna
  AI is a portfolio company of EQT Ventures.'
deliveryModel:
  model: saas
  open_source: false
  commercial: true
  callable_host: true
  label: Hosted service · you call their endpoint
  confidence: high
  source:
  - openapi
  - pricing
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source:
  - authentication
  - rate-limits
  - security
  generated: '2026-09-03'
  method: derived
image: https://framerusercontent.com/images/tM3dYw39zvWf45dsZXfTkZm0jNc.png
url: https://raw.githubusercontent.com/api-evangelist/pruna-ai/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- eqt-ventures
x-tier: stub
x-tier-reason: portfolio-lead
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-20'
x-enrichment:
  date: '2026-07-20'
  status: enriched
  artifacts_added: 19
  pass: local-v1
tags:
- Company
- Artificial Intelligence
- Machine-Learning
- Image-Generation
- Video Generation
- Generative AI
- Model Optimization
- Inference
- Developer Tools
tags_raw:
- Company
- Artificial Intelligence
- Machine Learning
- Image Generation
- Video Generation
- Generative AI
- Model Optimization
- Inference
- Developer Tools
apis:
- aid: pruna-ai:pruna-ai-content-delivery-api
  name: Pruna AI Content Delivery API
  description: Download generated content files
  humanURL: https://docs.api.pruna.ai/
  baseURL: https://api.pruna.ai
  tags:
  - Content Delivery
  properties:
  - type: OpenAPI
    url: openapi/pruna-ai-content-delivery-api-openapi.yml
  - type: Documentation
    url: https://docs.api.pruna.ai/
  - type: APIReference
    url: https://docs.api.pruna.ai/apis/models-api-0/versions/d086a242-3813-4148-a087-e724d4b333f8
  - type: GettingStarted
    url: https://docs.api.pruna.ai/guides/quickstart
- aid: pruna-ai:pruna-ai-file-management-api
  name: Pruna AI File Management API
  description: Upload files to be used as input for predictions
  humanURL: https://docs.api.pruna.ai/
  baseURL: https://api.pruna.ai
  tags:
  - File Management
  properties:
  - type: OpenAPI
    url: openapi/pruna-ai-file-management-api-openapi.yml
  - type: Documentation
    url: https://docs.api.pruna.ai/
  - type: APIReference
    url: https://docs.api.pruna.ai/apis/models-api-0/versions/d086a242-3813-4148-a087-e724d4b333f8
  - type: GettingStarted
    url: https://docs.api.pruna.ai/guides/quickstart
- aid: pruna-ai:pruna-ai-predictions-api
  name: Pruna AI Predictions API
  description: Core prediction workflow operations
  humanURL: https://docs.api.pruna.ai/
  baseURL: https://api.pruna.ai
  tags:
  - Predictions
  properties:
  - type: OpenAPI
    url: openapi/pruna-ai-predictions-api-openapi.yml
  - type: Documentation
    url: https://docs.api.pruna.ai/
  - type: APIReference
    url: https://docs.api.pruna.ai/apis/models-api-0/versions/d086a242-3813-4148-a087-e724d4b333f8
  - type: GettingStarted
    url: https://docs.api.pruna.ai/guides/quickstart
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Overlay
  url: overlays/pruna-ai-openapi-overlay.yaml
- type: DeveloperPortal
  url: https://docs.api.pruna.ai/
- type: Documentation
  url: https://docs.pruna.ai/en/stable/
- type: APIReference
  url: https://docs.api.pruna.ai/apis/models-api-0/versions/d086a242-3813-4148-a087-e724d4b333f8
- type: GettingStarted
  url: https://docs.api.pruna.ai/guides/quickstart
- type: SignUp
  url: https://dashboard.pruna.ai/login
- type: Pricing
  url: https://www.pruna.ai/pricing
- type: Blog
  url: https://www.pruna.ai/blog
- type: Support
  url: https://discord.gg/JFQmtFKCjd
- type: GitHubOrganization
  url: https://github.com/PrunaAI
- type: TermsOfService
  url: https://docs.api.pruna.ai/terms
- type: PrivacyPolicy
  url: https://www.pruna.ai/privacy-notice
- type: Sandbox
  url: https://demo.pruna.ai/
- type: Authentication
  url: authentication/pruna-ai-authentication.yml
- type: Conventions
  url: conventions/pruna-ai-conventions.yml
- type: ErrorCatalog
  url: errors/pruna-ai-problem-types.yml
- type: Lifecycle
  url: lifecycle/pruna-ai-lifecycle.yml
- type: Conformance
  url: conformance/pruna-ai-conformance.yml
- type: DataModel
  url: data-model/pruna-ai-data-model.yml
- type: RateLimits
  url: rate-limits/pruna-ai-rate-limits.yml
- type: Packages
  url: packages/pruna-ai-packages.yml
- type: SDKs
  url: packages/pruna-ai-packages.yml
- type: X-MCPServerCandidate
  url: mcp/pruna-ai-mcp.yml
  note: 'Renamed from MCPServer 2026-09-03 (roadmap#247): the manifest self-describes as status: candidate — a tool list derived
    from the published API contracts, not an existing server. The scorer already read the manifest and reported mcp_server
    correctly; the MCPServer type was crediting the artifact-type surfaces with a server that does not exist.'
- type: LLMsTxt
  url: llms/pruna-ai-llms.txt
- type: AgentSkill
  url: skills/_index.yml
- type: AgenticAccess
  url: agentic-access/pruna-ai-agentic-access.yml
- type: DomainSecurity
  url: security/pruna-ai-domain-security.yml
- type: Website
  url: https://www.pruna.ai/

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