Inference

Inference (inference.net) is an AI infrastructure platform for AI-native teams. It offers an OpenAI-compatible inference API for open-source, frontier, and custom fine-tuned language models, alongside Catalyst — its observability, tracing, evaluation, training, and deployment platform. Developers call chat completions, batch/async inference, function calling, structured outputs, and vision endpoints at https://api.inference.net/v1 using a Bearer API key; route and monitor traffic through the Catalyst Gateway; fine-tune and deploy custom models; and optimize agents end to end with HALO. The platform ships a first-party CLI (inf), a hosted MCP server, and webhooks for asynchronous inference. Backed by Multicoin Capital.

Inference is listed with 1 API on the APIs.io network. Tagged areas include Company, Artificial Intelligence, Machine Learning, LLM, and Inference.

The Inference catalog on APIs.io includes 1 event-driven AsyncAPI specification.

Inference’s developer surface includes documentation, API reference, getting-started guide, engineering blog, pricing, signup flow, authentication, and 18 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

55.9/100 strong ▬ flat Agent 47/100 agent ready Front door AI 6/6 dominant Heartbeat 100/100 alive saas Full breakdown ↓
scored 2026-11-06 · rubric v0.27.0 · Show this score on your site →

AccessFreemiumSelf serve⚡ Free to try

1 API 1 MCP Servers

Company Artificial Intelligence Machine Learning LLM Inference Observability Model Training Model Deployment MCP

Kin Score

Kin Score How this is scored →
scored 2026-11-06 · rubric v0.27.0

Composite quality — 55.9/100 · strong

Contract Quality 8.3 / 21

Developer Ergonomics 10.1 / 17

Access Clarity 15.0 / 17

Operational Transparency 4.7 / 11

Contract Governance 1.9 / 10

Discoverability 6.4 / 9

Regulatory Posture 3.8 / 15

Agent readiness — 47/100 · agent ready

Machine-Readable Contract 18 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 12 / 12

Machine-Readable Auth 10 / 10

Idempotency 0 / 9

Stable Error Semantics 0 / 8

Request/Response Examples 0 / 7

Rate-Limit Signaling 7 / 7

Typed Event Surface 6 / 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 6 / 6

Protected Resource Metadata 5 / 5

Registration Without a Human 6 / 6

Agentic Commerce Well-Known Document 0 / 5

Pagination 5 / 5

Distinct Operations 3 / 3

MCP Tool Quality 6 / 6

Regulatory Posture applies to this provider. Its tags matched the Horizontal (data, software, accessibility, platform) regime, so Regulatory Posture carries 15 points of the composite. If this regime is wrong for your business, say so on your provider repo — the applicability map is public and we will correct it.

Create-or-Update Ergonomics could not be measured. We hold no machine-readable contract for this provider to read, so there is nothing to measure a write surface against. Excluded rather than scored zero: never-measured and measured-empty are different facts. Publishing an OpenAPI is what makes this facet — and several others — scorable at all.

The six quality facets above are damped to 85 points between them, because the conditional facet above carries the other 15. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 85% of its nominal weight, not 100%. The full arithmetic is at apis.io/rating/.

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Agent readiness — checks not met, largest first (exact, from this profile):

Agentic Access Contract +10 pts — agentic_access artifact present (x-agentic-access), graded by author
Idempotency +9 pts — OpenAPI mutating operations declare an idempotency key — a header, a request-body property, or a named de-duplication token whose own description says so (verified); else common[].type matches /idempoten/i (documented)
Stable Error Semantics +8 pts — OpenAPI $refs a shared error schema across 4xx/5xx responses (verified), else common[].type includes ErrorCatalog / ErrorCodes / DeclineCodes
A2A Agent Card +8 pts — a2a/-a2a.yml manifest, graded on conformance.grade against A2A 1.0.0
Request/Response Examples +7 pts — share of operations carrying request/response examples; else an Examples / Code Samples link
Documented Reversibility +6 pts — a reversal operation in the contract, graded up when a window is documented too

5 more unmet checks in the Agent Readiness table above.

Kin Score — facets with the most composite points still available (weight × headroom):

Contract Quality scores 39.0 — up to +15.3 composite points
Contract Governance scores 18.2 — up to +9.8 composite points
Developer Ergonomics scores 59.5 — up to +8.1 composite points

Each check links to what satisfies it. Publish the artifact, or tell us where it already lives, and the score moves on the next scoring run.

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 the provider profile at artifacts.apis.io/inference/apis.yml: open an issue on github.com/api-evangelist/inference to ask a question or point us at an artifact you publish. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

Markets this provider is in provisional

The Kin Score Market layer reads a provider inside its market: its position, and how deep its integrations go. Depth is only comparable within a position. Provisional and unweighted: not part of the Kin Score or agent readiness.

Market	Position	Depth	Registered MCP server	Declares compatibility
MLOps and AI/ML Infrastructure (LF AI & Data, MLPerf, Kubeflow)	undeclared	-	-	1

Registered MCP server and declares compatibility are report only — not weighted. Undeclared means we found nothing we can read, so there is no number: we never infer integrations.

Standards implemented 4

Standards this provider implements or carries. De facto ones are profiled and measured by the API Commons; formal ones come from the standards directory and are linked by the provider's own tags. The evidence column says how each claim was established — not that it was made.

Model Context Protocol (MCP)

measured — observed by APIs.io (verified)

The OpenAI Interface

prose — states compatibility; nothing published to check it against

2 core of 338 operations graded · api-commons/models

OAuth 2.0 Protected Resource Metadata

measured — observed by APIs.io (verified)

Dynamic Client Registration

measured — observed by APIs.io (published)

APIs 1

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

Inference.net API

OpenAI-compatible inference API for open-source, frontier, and custom language models — chat completions, batch/async inference, function calling, structured outputs, and vision...

MCP Servers 1

Model Context Protocol servers that expose these APIs to AI agents.

Inference MCP Server

The Inference MCP server lets compatible AI coding assistants query and operate Catalyst resources (projects, agents, models, datasets, rubrics, evals, training jobs, deployment...

MCP SERVER

Inference API pricing

Prices published by Inference, read 2026-10-28 from inference.net/pricing/.

Plan	Price
Pay as you go	$0 + usage Includes: 1M included Gateway requests, 1M / mo Tracing spans, 14-day data retention, 1 seat
Growth	$250 per month Includes: $50 one-time opening credit, 50M / mo Gateway requests, 50M / mo Tracing spans, Unlimited data reten
Enterprise	Contact sales Includes: Custom contracts and committed-use pricing, dedicated infrastructure, direct support, custom models

Plan details, limits and sources →

Billed by: subscription · FinOps profile →

Pricing Plans 2

Published pricing tiers and plan structures.

Inference Plans

3 plans

PLANS

Inference Price Estimates

0 plans

PLANS

Rate Limits 1

Documented rate limits and quota policies.

Inference Rate Limits

4 limits

RATE LIMITS

FinOps 1

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

Inference Finops

FINOPS

Event Specifications 1

AsyncAPI definitions for this provider's event-driven and streaming APIs.

Inference Webhooks

ASYNCAPI

Security Posture 2

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

Inference Authentication

apiKey · 1 scheme

SECURITY

Inference Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Resources

Get Started 4

Portal, sign-up, and the first successful call

DeveloperPortal

DeveloperPortal

GettingStarted

GettingStarted

SignUp

SignUp

Login

Documentation 2

Reference material describing how the API behaves

Documentation

Documentation

APIReference

APIReference

Agent Surfaces 2

MCP servers, agent skills, and machine-readable catalogs

MCPServer

MCPServer

LLMsTxt

LLMsTxt

Design & Contract 4

Pagination, idempotency, versioning, errors, and events

Conventions

Lifecycle

Webhooks

Conformance

Build 3

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

GitHubOrganization

CLI

CLI

Packages

Packages

Access & Security 3

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

TrustCenter

TrustCenter

Authentication

Authentication

Operate 1

Status, limits, changes, and where to get help

RateLimits

RateLimits

Commercial 4

Pricing, plans, and the legal terms of use

Pricing

TermsOfService

PrivacyPolicy

Plans

Company 2

The organization behind the API

Website

Website

Blog

Blog

Source (apis.yml)

aid: inference
name: Inference
description: Inference (inference.net) is an AI infrastructure platform for AI-native teams. It offers an OpenAI-compatible
  inference API for open-source, frontier, and custom fine-tuned language models, alongside Catalyst — its observability,
  tracing, evaluation, training, and deployment platform. Developers call chat completions, batch/async inference, function
  calling, structured outputs, and vision endpoints at https://api.inference.net/v1 using a Bearer API key; route and monitor
  traffic through the Catalyst Gateway; fine-tune and deploy custom models; and optimize agents end to end with HALO. The
  platform ships a first-party CLI (inf), a hosted MCP server, and webhooks for asynchronous inference. Backed by Multicoin
  Capital.
url: https://raw.githubusercontent.com/api-evangelist/inference/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- multicoin-capital
x-tier: profiled
x-tier-reason: enrichment-pipeline
deliveryModel:
  model: saas
  open_source: false
  commercial: true
  callable_host: false
  label: Hosted service · you call their endpoint
  confidence: medium
  source:
  - pricing
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: freemium
  onboarding: self-serve
  trial: false
  try_now: true
  public: false
  gated: none
  gated_source:
  - onboarding
  label: Freemium · Self-serve signup
  confidence: high
  source:
  - plans
  - authentication
  - rate-limits
  - security
  generated: '2026-11-06'
  method: derived
image: https://inference.net/og/home.png
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-19'
tags:
- Company
- Artificial Intelligence
- Machine Learning
- LLM
- Inference
- Observability
- Model Training
- Model Deployment
- MCP
tags_raw:
- Company
- Artificial Intelligence
- Machine Learning
- LLM
- Inference
- Observability
- Model Training
- Model Deployment
- MCP
- Machine-Learning
apis:
- name: Inference.net API
  description: OpenAI-compatible inference API for open-source, frontier, and custom language models — chat completions, batch/async
    inference, function calling, structured outputs, and vision — authenticated with a Bearer API key.
  humanURL: https://docs.inference.net/api/api-quickstart
  baseURL: https://api.inference.net/v1
  tags:
  - LLM
  - Inference
  - OpenAI-Compatible
  tags_raw:
  - LLM
  - Inference
  - OpenAI Compatible
  properties:
  - type: Documentation
    url: https://docs.inference.net
  - type: APIReference
    url: https://docs.inference.net/api/api-quickstart
  - type: Authentication
    url: https://docs.inference.net/reference/api-keys
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: DomainSecurity
  url: security/inference-domain-security.yml
- type: Website
  url: https://inference.net
- type: DeveloperPortal
  url: https://docs.inference.net
- type: Documentation
  url: https://docs.inference.net
- type: APIReference
  url: https://docs.inference.net/api/api-quickstart
- type: GettingStarted
  url: https://docs.inference.net/api/api-quickstart
- type: Blog
  url: https://inference.net/blog
- type: Pricing
  url: https://inference.net/pricing
- type: SignUp
  url: https://inference.net/register
- type: Login
  url: https://inference.net/signin
- type: TermsOfService
  url: https://inference.net/terms-of-service
- type: PrivacyPolicy
  url: https://inference.net/privacy-policy
- type: GitHubOrganization
  url: https://github.com/context-labs
- type: TrustCenter
  url: https://trust.inference.net
- type: Authentication
  url: authentication/inference-authentication.yml
- type: RateLimits
  url: rate-limits/inference-rate-limits.yml
- type: Plans
  url: plans/inference-plans.yml
- type: MCPServer
  url: mcp/inference-mcp.yml
- type: CLI
  url: cli/inference-cli.yml
- type: Packages
  url: packages/inference-packages.yml
- type: Conventions
  url: conventions/inference-conventions.yml
- type: Lifecycle
  url: lifecycle/inference-lifecycle.yml
- type: Webhooks
  url: asyncapi/inference-webhooks.yml
- type: Conformance
  url: conformance/inference-conformance.yml
- type: LLMsTxt
  url: llms/inference-llms.txt
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence
x-tags-removed:
- Crypto Web3

Inference API — frequently asked questions

Does Inference have an API?

Yes. APIs.io lists 1 API from Inference, including Inference.net API.

How do I authenticate with the Inference API?

Inference documents its authentication (apiKey · 1 scheme). The details are profiled on APIs.io as Inference Authentication.

How much does the Inference API cost?

Inference publishes its prices; its Pay as you go plan is $0 + usage as of 2026-10-28. APIs.io lists 3 pricing plans for Inference, with each plan's price, limits and inclusions under Pricing on this page.

Does Inference have an MCP server?

Yes. APIs.io lists 1 MCP server for Inference: The Inference MCP server lets compatible AI coding assistants query and operate Catalyst resources (projects, agents, models, datasets, rubrics, evals, training jobs, deployments, inferences, traces,

Is the Inference API ready for AI agents?

Inference has a Kin Score of 55.9 out of 100 (strong) and an Agent Readiness score of 47.1 (agent-ready), scored by API Evangelist on 2026-11-06.

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