AIMLAPI
AIMLAPI is a unified AI model API gateway providing access to 400+ state-of-the-art AI models from OpenAI, Anthropic, Google, Meta, DeepSeek, Mistral, Stability AI, and 40+ other providers through a single OpenAI-compatible API. Supported modalities include text/chat LLMs, image generation, video generation, music generation, speech-to-text, text-to-speech, vision/OCR, embeddings, and 3D generation.
Real signal across most facets with visible, nameable gaps — the contract exists but is thin, or the portal is good while governance and commercial terms are absent.
API Evangelist profiles AIMLAPI the way a machine reads it — 64 machine-readable artifacts across 10 APIs, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — AIMLAPI scores 58.9/100 (developing), with a separate agent-readiness read of 48/100 (agent ready). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.
Kin Score
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile AIMLAPI
Each block below is one kind of artifact we hold for AIMLAPI. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
APIs 10
Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.
Individual APIs this provider publishes, each with its own machine-readable definition.
AIMLAPI API Key Management API
## **Creating an API Key** To create a new API key Sign-ip to [app.aimlapi.com](https://app.aimlapi.com), navigate to Key Management page and create an API Key Note that your Ke...
AIMLAPI Assistants API
The Assistants API from AIMLAPI — 2 operation(s) for assistants.
AIMLAPI Chat API
The Chat API from AIMLAPI — 1 operation(s) for chat.
AIMLAPI Images API
Given a prompt and/or an input image, the model will generate a new image.
AIMLAPI Models API
List and describe the various models available in the API. You can refer to the [Models](https://aimlapi.com/models) documentation to understand what models are available and th...
AIMLAPI Threads API
The Threads API from AIMLAPI — 1 operation(s) for threads.
AIMLAPI Threads > Messages API
The Threads > Messages API from AIMLAPI — 2 operation(s) for threads > messages.
AIMLAPI Threads > Runs API
The Threads > Runs API from AIMLAPI — 2 operation(s) for threads > runs.
AIMLAPI Voice API
The Voice API from AIMLAPI — 2 operation(s) for voice.
AIMLAPI [WIP] Completions API
The [WIP] Completions API from AIMLAPI — 1 operation(s) for [wip] completions.
Scroll within the panel for all 10 ·
Open Collections 1
Open, tool-agnostic collections carry the same runnable value as Postman without locking you to one client — the portable, forkable form of the same exercise.
Open, tool-agnostic API collections (OpenAPI-derived and Bruno).
AIMLAPI AI/ML API Documentation
OPEN COLLECTIONGraphQL 1
Where a provider ships GraphQL, the schema is the contract. We profile it alongside the REST surface so the whole interface is legible in one place.
GraphQL schemas published by this provider.
AIMLAPI GraphQL API
AIMLAPI is an AI model aggregation API providing access to 200+ AI models including GPT-4, Claude, Llama, Stable Diffusion, Midjourney, and more through a single OpenAI-compatib...
GRAPHQLPricing Plans 1
Pricing is part of the interface. Machine-readable plans tell you what a tier costs and includes before you commit — one of the six things the Kin Score reads for commercial clarity.
Published pricing tiers and plan structures.
Rate Limits 1
Rate limits are the difference between a demo that works and a production integration that doesn't fall over. Publishing them is an operational-transparency signal — and a hard requirement for any agent that plans its own throughput.
Documented rate limits and quota policies.
Aimlapi Rate Limits
RATE LIMITSFinOps 1
Cost, billing, and metering signals let a buyer model the financial operations of an API before it's live. We profile them for the same reason we profile pricing: the money is part of the contract.
Cost, billing, and metering signals for API financial operations.
Aimlapi Finops
FINOPSFeatures 10
The notable capabilities this provider advertises, captured as structured features so they can be searched and compared instead of read one landing page at a time.
Notable capabilities this provider offers.
400+ AI Models
Access to 400+ models from OpenAI, Anthropic, Google, Meta, DeepSeek, Mistral, Stability AI, and 40+ providers.
OpenAI-Compatible API
Drop-in replacement for OpenAI API — use existing OpenAI client libraries with AIMLAPI endpoint.
Text and Chat Completions
Chat completions, completion, function calling, streaming, reasoning, and code generation.
Image Generation
Generate images via DALL-E, Flux, Stable Diffusion, and other image generation models.
Video Generation
Generate video via Sora 2, Runway, and other video generation models.
Speech Models
Text-to-speech and speech-to-text transcription via Whisper and other speech models.
Music Generation
AI music generation via dedicated music models.
Vision and OCR
Image understanding, visual question answering, and OCR via vision-capable LLMs.
Embeddings
Generate vector embeddings for semantic search and RAG applications.
Playground
Online playground for experimenting with all available models without writing code.
Scroll within the panel for all 10 ·
Semantic Vocabularies 1
JSON-LD contexts give the data shared meaning across APIs. We profile them because semantics are what let a machine reconcile 'customer' here with 'customer' somewhere else.
JSON-LD contexts and semantic vocabularies used across these APIs.
Aimlapi Context
JSON-LDSpectral Rules 2
Governance rulesets we run against this provider's specs — the automated checks behind parts of the score. Profiling them makes the quality bar explicit and re-runnable, not a matter of opinion.
AIMLAPI API Rules
SPECTRALAIMLAPI API Rules
SPECTRALJSON Schema 7
Standalone JSON Schema definitions describe the data models behind the API. We profile them so the shapes are validatable on their own — useful long after a single request is forgotten.
Standalone JSON Schema definitions for this provider's data models.
ApiKey
JSON SCHEMAChatCompletionRequest
JSON SCHEMAChatCompletionResponse
JSON SCHEMAEmbeddingRequest
JSON SCHEMAImageGenerationRequest
JSON SCHEMAMessage
JSON SCHEMAModelInfo
JSON SCHEMAScroll within the panel for all 7 ·
JSON Structure 7
JSON Structure captures the data shapes in a form built for tooling — a complement to JSON Schema that keeps the model machine-legible.
JSON Structure definitions describing this provider's data shapes.
Aimlapi Api Key Structure
JSON STRUCTUREAimlapi Chat Completion Request Structure
JSON STRUCTUREAimlapi Chat Completion Response Structure
JSON STRUCTUREAimlapi Embedding Request Structure
JSON STRUCTUREAimlapi Image Generation Request Structure
JSON STRUCTUREAimlapi Message Structure
JSON STRUCTUREAimlapi Model Info Structure
JSON STRUCTUREScroll within the panel for all 7 ·
Examples 7
Real request and response payloads are what turn a spec from abstract into obvious — and they're one of the twelve things an agent needs to call an API correctly on the first try.
Example request and response payloads for these APIs.
Scroll within the panel for all 7 ·
Security Posture 2
Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Agentic Access 1
An x-agentic-access contract marks which operations are safe for an agent to run on its own and which need a human in the loop. It is the difference between an API an agent can use and one it can use safely.
Recommended x-agentic-access execution contracts for AI agents.
Use Cases 6
What developers actually build with this provider — captured so the catalogue answers 'what is this for', not just 'what does this expose'.
What developers build with this provider.
AI Chatbot Development
Build conversational AI chatbots and virtual assistants using leading LLMs.
Content Generation
Automate text, image, video, and music content generation for media and marketing.
RAG Applications
Build retrieval-augmented generation applications using embeddings and LLMs.
Code Generation
Integrate AI code generation and review capabilities into developer tools.
Document Processing
Extract information and summarize documents using vision and LLM models.
Voice Applications
Add speech-to-text transcription and text-to-speech synthesis to applications.
Integrations 6
Pre-built integrations with other platforms tell you where this provider already fits in a stack.
Pre-built integrations with other platforms and tools.
OpenAI SDK
Use the official OpenAI Python and Node.js SDKs with AIMLAPI base URL.
LangChain
Integrate AIMLAPI models with LangChain for agentic AI workflows.
LlamaIndex
Use AIMLAPI with LlamaIndex for RAG and document intelligence pipelines.
Vercel AI SDK
Build AI-powered web apps using Vercel AI SDK with AIMLAPI as backend.
Python
Native Python integration via requests library or OpenAI client.
Node.js
Node.js integration via OpenAI npm package pointed at AIMLAPI endpoint.
Resources
Every other property we hold for AIMLAPI — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Get Started 1
Portal, sign-up, and the first successful call
Documentation 1
Reference material describing how the API behaves
Agent Surfaces 2
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 2
Pagination, idempotency, versioning, errors, and events
Build 1
SDKs, sample code, and the tooling you integrate with
Access & Security 2
Authentication, authorization, and security posture
Operate 2
Status, limits, changes, and where to get help
Commercial 3
Pricing, plans, and the legal terms of use
Company 2
The organization behind the API
Other 1
Properties that don't map to a standard resource type
← All providers · Data indexed from github.com/api-evangelist/aimlapi · machine-readable index on apis.io