Preferred Networks

Preferred Networks, Inc. (PFN) is a Tokyo-based AI company founded in March 2014 that vertically integrates the AI value chain from its own MN-Core AI processors and supercomputing infrastructure through to generative-AI foundation models, solutions and products. PFN develops PLaMo, a Japanese large language model built fully from scratch, and offers it commercially through the cloud-hosted PLaMo API — an OpenAI-compatible chat-completions, tokenize and models service at api.platform.preferredai.jp — alongside on-premises, Amazon Bedrock Marketplace, Snowflake and edge (PLaMo Lite) deployment options. PFN also maintains widely used open-source machine-learning software including Optuna, Chainer, PFRL, pytorch-pfn-extras and the PLaMo Translate CLI, which doubles as a locally hosted MCP server.

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

Preferred Networks’ developer surface includes documentation, API reference, getting-started guide, support, engineering blog, pricing, signup flow, and 22 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

41.2/100 developing ▬ flat Agent 10/100 agent aware Front door AI 1/6 silent 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 Generative AI Inference Foundation Models Japan Semiconductors Supercomputing Translation MCP

Kin Score

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

Composite quality — 41.2/100 · developing

Contract Quality 1.4 / 21

Developer Ergonomics 9.3 / 17

Access Clarity 9.8 / 17

Operational Transparency 6.4 / 11

Contract Governance 1.9 / 10

Discoverability 5.5 / 9

Regulatory Posture 3.5 / 15

Agent readiness — 10/100 · agent aware

Machine-Readable Contract 0 / 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 7 / 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
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
Registration Without a Human +6 pts — a `registration_endpoint` in the served RFC 8414 / OIDC discovery document

9 more unmet checks in the Agent Readiness table above.

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

Contract Quality scores 6.5 — up to +23.4 composite points
Contract Governance scores 18.2 — up to +9.8 composite points
Developer Ergonomics scores 54.8 — up to +9.0 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/preferred-networks/apis.yml: open an issue on github.com/api-evangelist/preferred-networks 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
Semiconductor Consortia (RISC-V, OCP hardware, CHIPS awards)	undeclared	-	-	-

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 2

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 (documented)

The OpenAI Interface

prose — states compatibility; nothing published to check it against

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

APIs 1

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

PLaMo API

The PLaMo API is Preferred Networks' cloud service for its domestically developed PLaMo large language models. Its interface is compatible with the OpenAI API, so existing OpenA...

MCP Servers 1

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

Preferred Networks MCP surface

Preferred Networks ships one real MCP server, and it is not for the PLaMo API. The first-party plamo-translate CLI starts an MCP server as part of its `server` command, exposing...

MCP SERVER

Preferred Networks API pricing

Prices published by Preferred Networks, read 2026-10-28 from plamo.preferredai.jp/api.

Plan	Price
Free	INPUT 0円 Includes: PLaMo APIの基本機能を無料で利用可能 ※利用量・レートリミットに制限あり；検索を1日60回・月200回まで無料（キャンペーン期間中、2026年11月30日まで）
Free (output)	OUTPUT 0円
Standard (input)	INPUT 60円 Includes: 128k tokensまでのInput/Output単価（128k tokens超はリリース記念期間中同額）
Standard (output)	OUTPUT 250円
Provider	INPUT Custom Includes: 用途・規模に応じて個別見積もり
On-Premise	提供方法を見る Includes: モデル本体のみ／Dockerイメージ／モデル＋サーバ一式／マーケットプレイス／PLaMo Lite

Plan details, limits and sources →

Billed by: 1m tokens (input) · FinOps profile →

Pricing Plans 1

Published pricing tiers and plan structures.

Preferred Networks Plans Pricing

6 plans

PLANS

Rate Limits 1

Documented rate limits and quota policies.

Preferred Networks Rate Limits

7 limits

RATE LIMITS

FinOps 1

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

Preferred Networks Finops

FINOPS

Security Posture 3

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

Preferred Networks Authentication

1 scheme

SECURITY

Preferred Networks Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Preferred Networks Trust Center

ISO/IEC 27001

SECURITY

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 2

MCP servers, agent skills, and machine-readable catalogs

MCPServer

MCPServer

LLMsTxt

LLMsTxt

Design & Contract 4

Pagination, idempotency, versioning, errors, and events

Conventions

Lifecycle

DataModel

Conformance

Build 4

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

Examples

Packages

CLI

Access & Security 3

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Authentication

Authentication

Compliance

Compliance

Operate 4

Status, limits, changes, and where to get help

Support

RateLimits

Deprecation

ChangeLog

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: preferred-networks
name: Preferred Networks
description: Preferred Networks, Inc. (PFN) is a Tokyo-based AI company founded in March 2014 that vertically integrates the
  AI value chain from its own MN-Core AI processors and supercomputing infrastructure through to generative-AI foundation
  models, solutions and products. PFN develops PLaMo, a Japanese large language model built fully from scratch, and offers
  it commercially through the cloud-hosted PLaMo API — an OpenAI-compatible chat-completions, tokenize and models service
  at api.platform.preferredai.jp — alongside on-premises, Amazon Bedrock Marketplace, Snowflake and edge (PLaMo Lite) deployment
  options. PFN also maintains widely used open-source machine-learning software including Optuna, Chainer, PFRL, pytorch-pfn-extras
  and the PLaMo Translate CLI, which doubles as a locally hosted MCP server.
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
  - sandbox
  generated: '2026-11-06'
  method: derived
image: https://www.preferred.jp/images/ogp.png
url: https://raw.githubusercontent.com/api-evangelist/preferred-networks/refs/heads/main/apis.yml
x-type: company
x-source: harvest:secondary-market
specificationVersion: '0.20'
created: '2026-08-26'
modified: '2026-08-26'
x-docs-platform: vitepress
x-docs-platform-confidence: medium
x-docs-platform-checked: 2026-10-04
x-docs-hosting: firebase
tags:
- Company
- Artificial Intelligence
- Machine Learning
- LLM
- Generative AI
- Inference
- Foundation Models
- Japan
- Semiconductors
- Supercomputing
- Translation
- MCP
tags_raw:
- Company
- Artificial Intelligence
- Machine Learning
- Large Language Models
- Generative AI
- LLM Inference
- Foundation Models
- Japan
- Semiconductors
- Supercomputing
- Translation
- MCP
- Machine-Learning
apis:
- name: PLaMo API
  description: The PLaMo API is Preferred Networks' cloud service for its domestically developed PLaMo large language models.
    Its interface is compatible with the OpenAI API, so existing OpenAI/LangChain client code works by pointing the base URL
    at https://api.platform.preferredai.jp/v1 and supplying a PLaMo API key as a bearer token. The published surface is three
    endpoints — Chat Completions (streaming SSE, function calling, JSON-Schema structured outputs and reasoning controls),
    Tokenize, and Models (index + retrieve) — served against the plamo-3.0-prime family.
  image: https://www.preferred.jp/images/ogp.png
  humanURL: https://docs.plamo.preferredai.jp/en/
  baseURL: https://api.platform.preferredai.jp/v1
  tags:
  - LLM
  - Generative AI
  - Chat Completions
  - OpenAI-Compatible
  - Tokenization
  - Japan
  tags_raw:
  - Large Language Models
  - Generative AI
  - Chat Completions
  - OpenAI Compatible
  - Tokenization
  - Japan
  properties:
  - type: Documentation
    url: https://docs.plamo.preferredai.jp/en/
  - type: APIReference
    url: https://docs.plamo.preferredai.jp/en/api
  - type: GettingStarted
    url: https://docs.plamo.preferredai.jp/en/getting-started
  - type: Console
    url: https://console.platform.preferredai.jp/
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: DomainSecurity
  url: security/preferred-networks-domain-security.yml
- type: Website
  url: https://www.preferred.jp/en/
- type: DeveloperPortal
  url: https://plamo.preferredai.jp/api
- type: Documentation
  url: https://docs.plamo.preferredai.jp/en/
- type: APIReference
  url: https://docs.plamo.preferredai.jp/en/api
- type: GettingStarted
  url: https://docs.plamo.preferredai.jp/en/getting-started
- type: Support
  url: https://support.plamo.preferredai.jp/hc/ja
- type: Blog
  url: https://tech.preferred.jp/en/blog/
- type: GitHubOrganization
  url: https://github.com/pfnet
- type: Pricing
  url: https://plamo.preferredai.jp/api
- type: SignUp
  url: https://plamo.preferredai.jp/signup
- type: TermsOfService
  url: https://plamo.preferredai.jp/info/terms
- type: PrivacyPolicy
  url: https://www.preferred.jp/en/policy/
- type: Examples
  url: https://github.com/pfnet-research/plamo-examples
- type: Plans
  url: plans/preferred-networks-plans-pricing.yml
- type: RateLimits
  url: rate-limits/preferred-networks-rate-limits.yml
- type: Authentication
  url: authentication/preferred-networks-authentication.yml
- type: Conventions
  url: conventions/preferred-networks-conventions.yml
- type: Lifecycle
  url: lifecycle/preferred-networks-lifecycle.yml
- type: Deprecation
  url: lifecycle/preferred-networks-lifecycle.yml
- type: ChangeLog
  url: changelog/preferred-networks-changelog.yml
- type: DataModel
  url: data-model/preferred-networks-data-model.yml
- type: Conformance
  url: conformance/preferred-networks-conformance.yml
- type: Compliance
  url: security/preferred-networks-trust-center.yml
- type: Packages
  url: packages/preferred-networks-packages.yml
- type: CLI
  url: cli/preferred-networks-cli.yml
- type: MCPServer
  url: mcp/preferred-networks-mcp.yml
- type: Sandbox
  url: sandbox/preferred-networks-sandbox.yml
- type: LLMsTxt
  url: llms/preferred-networks-llms.txt
x-enrichment:
  date: '2026-08-26'
  status: enriched
  artifacts_added: 16
  pass: local-v1

Preferred Networks API — frequently asked questions

Does Preferred Networks have an API?

Yes. APIs.io lists 1 API from Preferred Networks, including PLaMo API.

How do I authenticate with the Preferred Networks API?

Preferred Networks uses bearer-token authentication (1 scheme). The details are profiled on APIs.io as Preferred Networks Authentication.

How much does the Preferred Networks API cost?

Preferred Networks publishes its prices; its Free plan is INPUT 0円 as of 2026-10-28. APIs.io lists 6 pricing plans for Preferred Networks, with each plan's price, limits and inclusions under Pricing on this page.

Does Preferred Networks have an MCP server?

Yes. APIs.io lists 1 MCP server for Preferred Networks: Preferred Networks ships one real MCP server, and it is not for the PLaMo API. The first-party plamo-translate CLI starts an MCP server as part of its `server` command, exposing the local plamo-2-tran

Is the Preferred Networks API ready for AI agents?

Preferred Networks has a Kin Score of 41.2 out of 100 (developing) and an Agent Readiness score of 9.7 (agent-aware), scored by API Evangelist on 2026-11-06.

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get_provider_toolsEvery MCP tool they ship, with the operation each wraps.
get_provider_evidenceHow each part of their score was established. Free — the basis for a claim should not sit behind it.
get_provider_ratingPRO — composite, band, trend and facet scores.
apis_io_searchSTART HERE — APIs, providers and tags for one query, each with its total.
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