Liquid AI

Liquid AI is an MIT spinoff developing Liquid Foundation Models (LFMs) - a new class of generative models based on liquid neural networks. Offers LFM2 (2.6B / 8B-A1B / 24B-A2B) and LFM2.5 (350M / 1.2B variants) with text, vision, audio, and thinking modes. The LEAP platform enables LFM customization and on-device deployment.

Liquid AI is listed with 1 API on the APIs.io network. Tagged areas include Artificial Intelligence, LLM, Inference, Foundation Models, and Liquid Networks.

Liquid AI’s developer surface includes engineering blog, documentation, and 9 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

14.8/100 emerging ▬ flat Agent 13/100 agent aware Front door AI 6/6 dominant Heartbeat 54/100 slowing saas Full breakdown ↓
scored 2026-11-13 · rubric v0.28.0 · Show this score on your site →

AccessEnterprise

1 API 1 MCP Servers

Artificial Intelligence LLM Inference Foundation ModelsLiquid NetworksEdge AI On-Device

Kin Score

Kin Score How this is scored →
scored 2026-11-13 · rubric v0.28.0

Composite quality — 14.8/100 · emerging

Contract Quality 0.0 / 21

Developer Ergonomics 5.3 / 17

Access Clarity 2.2 / 17

Operational Transparency 1.0 / 11

Contract Governance 0.0 / 10

Discoverability 6.4 / 9

Regulatory Posture 0.0 / 15

Agent readiness — 13/100 · agent aware

Machine-Readable Contract 0 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 12 / 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 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 AI & Biometrics 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):

Machine-Readable Contract +18 pts — api_specs includes an OpenAPI document Ask about this →
Agentic Access Contract +10 pts — agentic_access artifact present (x-agentic-access), graded by author Ask about this →
Machine-Readable Auth +10 pts — a served openid-configuration/oauth-authorization-server carrying `issuer` (served), else the securitySchemes class in the provider OpenAPIs — bound (mutualTLS, DPoP, Signature) > negotiable (oauth2 authorizationCode/clientCredentials, openIdConnect) > bearer (http bearer, apiKey) Ask about this →
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) Ask about this →
Stable Error Semantics +8 pts — OpenAPI $refs a shared error schema across 4xx/5xx responses (verified), else common[].type includes ErrorCatalog / ErrorCodes / DeclineCodes Ask about this →
A2A Agent Card +8 pts — a2a/-a2a.yml manifest, graded on conformance.grade against A2A 1.0.0 Ask about this →

11 more unmet checks in the Agent Readiness table above.

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

Contract Quality scores 0.0 — up to +25.0 composite points Ask about this →
Access Clarity scores 12.8 — up to +17.4 composite points Ask about this →
Developer Ergonomics scores 31.0 — up to +13.8 composite points Ask about this →

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.

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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/liquid-ai/apis.yml: open an issue on github.com/api-evangelist/liquid-ai 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 →

Standards implemented 1

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)

APIs 1

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

Liquid AI Platform API

Hosted inference and customization API for the LFM family. Includes Liquid Playground and LEAP customization/deployment platform. LFM models also distributed on Hugging Face and...

MCP Servers 1

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

Liquid AI MCP Server

Remote MCP server at docs.liquid.ai over HTTP; 3 tools listed.

MCP SERVER

Liquid AI API pricing

Not yet checked against Liquid AI's own pricing page. Compiled by API Evangelist on 2026-05-08 from www.liquid.ai/; confirm before you rely on a figure.

Plan	Price
To Be Reconciled enterprise	—

Plan details, limits and sources →

Rate limits

Default: see provider documentation varies

Compiled by API Evangelist, not yet checked against Liquid AI's documentation. Rate-limit details →

Pricing Plans 1

Published pricing tiers and plan structures.

Liquid AI Plans Pricing

1 plans

PLANS

Rate Limits 1

Documented rate limits and quota policies.

Liquid AI Rate Limits

1 limits

RATE LIMITS

FinOps 1

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

Liquid AI Finops

FINOPS

Security Posture 1

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

Liquid AI Domain Security

TLSv1.3 · HSTS · DNSSEC · DMARC

SECURITY

Resources

Documentation 1

Reference material describing how the API behaves

Documentation

Documentation

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

LlmsText

LlmsText

Build 1

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

GitHubOrganization

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Operate 1

Status, limits, changes, and where to get help

RateLimits

RateLimits

Commercial 2

Pricing, plans, and the legal terms of use

Plans

Plans

FinOps

FinOps

Company 3

The organization behind the API

Blog

Blog

LinkedIn

Website

Website

Other 1

Properties that don't map to a standard resource type

HuggingFace

HuggingFace

Source (apis.yml)

aid: liquid-ai
url: https://raw.githubusercontent.com/api-evangelist/liquid-ai/refs/heads/main/apis.yml
name: Liquid AI
kind: company
description: Liquid AI is an MIT spinoff developing Liquid Foundation Models (LFMs) - a new class of generative models based
  on liquid neural networks. Offers LFM2 (2.6B / 8B-A1B / 24B-A2B) and LFM2.5 (350M / 1.2B variants) with text, vision, audio,
  and thinking modes. The LEAP platform enables LFM customization and on-device deployment.
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: enterprise
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Enterprise
  confidence: low
  source:
  - plans
  - security
  generated: '2026-11-13'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/liquid-ai.png
x-docs-platform: mintlify
x-docs-platform-confidence: medium
x-docs-platform-checked: 2026-10-03
tags:
- Artificial Intelligence
- LLM
- Inference
- Foundation Models
- Liquid Networks
- Edge AI
- On-Device
tags_raw:
- AI
- LLM
- Inference
- Foundation Models
- Liquid Networks
- Edge AI
- On-Device
created: '2026-05-08'
modified: '2026-10-06'
specificationVersion: '0.23'
apis:
- aid: liquid-ai:platform
  name: Liquid AI Platform API
  description: Hosted inference and customization API for the LFM family. Includes Liquid Playground and LEAP customization/deployment
    platform. LFM models also distributed on Hugging Face and via OpenRouter for hosted inference (e.g. LFM2-24B-A2B at $0.03/M
    input, $0.12/M output; LFM2.5-1.2B-Instruct/Thinking free).
  image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/apis-json-logo.jpg
  humanURL: https://docs.liquid.ai/
  baseURL: https://api.liquid.ai
  tags:
  - Artificial Intelligence
  - LLM
  - Chat Completions
  - Vision
  - Audio
  - Edge AI
  - On-Device
  tags_raw:
  - AI
  - LLM
  - Chat Completions
  - Vision
  - Audio
  - Edge AI
  - On-Device
  properties:
  - type: Documentation
    url: https://docs.liquid.ai/
  - type: GettingStarted
    url: https://docs.liquid.ai/lfm/getting-started/welcome
  - type: Pricing
    url: https://www.liquid.ai/pricing
  - type: Playground
    url: https://demos.liquid.ai/
  - type: HuggingFace
    url: https://huggingface.co/LiquidAI
  - type: LEAP
    url: https://www.liquid.ai/
common:
- url: https://www.liquid.ai/engineering
  type: Blog
- type: DomainSecurity
  url: security/liquid-ai-domain-security.yml
- type: GitHubOrganization
  url: https://github.com/Liquid4All
- type: LinkedIn
  url: https://www.linkedin.com/company/liquid-ai-inc
- type: Website
  url: https://www.liquid.ai/
- type: Documentation
  url: https://docs.liquid.ai/
- type: HuggingFace
  url: https://huggingface.co/LiquidAI
- type: Plans
  url: plans/liquid-ai-plans-pricing.yml
- type: RateLimits
  url: rate-limits/liquid-ai-rate-limits.yml
- type: FinOps
  url: finops/liquid-ai-finops.yml
- type: LlmsText
  url: https://docs.liquid.ai/llms.txt
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com

Liquid AI API — frequently asked questions

Does Liquid AI have an API?

Yes. APIs.io lists 1 API from Liquid AI, including Liquid AI Platform API.

How much does the Liquid AI API cost?

APIs.io lists 1 pricing plan for Liquid AI, with each plan's price, limits and inclusions under Pricing on this page.

Does Liquid AI have an MCP server?

Yes. APIs.io lists 1 MCP server for Liquid AI: Remote MCP server at docs.liquid.ai over HTTP; 3 tools listed.

Is the Liquid AI API ready for AI agents?

Liquid AI has a Kin Score of 14.8 out of 100 (emerging) and an Agent Readiness score of 13.0 (agent-aware), scored by API Evangelist on 2026-11-13.

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