FuriosaAI

FuriosaAI is a South Korean semiconductor company that designs data-center AI inference chips and the software stack that runs on them. Its second-generation NPU, RNGD, implements a Tensor Contraction Processor architecture on TSMC 5nm and targets LLM, multi-modal and vision inference. The developer surface is software you run yourself rather than a hosted API: Furiosa-LLM ships an OpenAI-compatible server exposing chat, completions, responses, embeddings, score, rerank, models, tokenizer and Prometheus metrics endpoints, and the earlier Furiosa Model Server implements the KServe v2 Predict Protocol and the Triton Model Repository extension over REST and gRPC. Around that sit Python, Go and Rust packages, a furiosa-smi device CLI, container images, an APT/RPM package repository, and a Kubernetes cloud-native toolkit (device plugin, DRA driver, feature discovery, metrics exporter, NPU operator).

FuriosaAI publishes 5 API contracts indexed on the APIs.io network, including Health API, Models API, Predict API, and 2 more. Tagged areas include Artificial Intelligence, Machine Learning, Inference, Semiconductors, and NPU.

The FuriosaAI catalog on APIs.io includes 1 Spectral governance ruleset.

FuriosaAI’s developer surface includes documentation, API reference, getting-started guide, support, engineering blog, changelog, signup flow, and 28 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

45.0/100 developing ▬ flat Agent 21/100 agent aware Front door AI 6/6 dominant Heartbeat 90/100 alive Full breakdown ↓
scored 2026-11-06 · rubric v0.27.0 · Show this score on your site →

AccessApproval

2 published contracts 3 Agent Skills

Artificial Intelligence Machine Learning Inference Semiconductors NPU Hardware LLM Model Serving Kubernetes Developer Tools Compute Infrastructure

What this lets a business do 1

Business capabilities this provider's published APIs can perform, derived from its own contracts. Browse all capabilities →

AI Model Services

AE-110

Models

POST /v2/models/${MODEL_NAME}/versions/${MODEL_VERSION}/infer

Kin Score

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

Composite quality — 45.0/100 · developing

Contract Quality 6.8 / 19

Developer Ergonomics 12.1 / 15

Access Clarity 3.6 / 15

Operational Transparency 3.1 / 10

Contract Governance 2.9 / 9

Discoverability 5.5 / 8

Regulatory Posture 2.9 / 15

Create-or-Update Ergonomics 0.0 / 10

Agent readiness — 21/100 · agent aware

Machine-Readable Contract 18 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 0 / 12

Machine-Readable Auth 10 / 10

Idempotency 0 / 9

Stable Error Semantics 8 / 8

Request/Response Examples 0 / 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

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 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.

The six quality facets above are damped to 75 points between them, because the conditional facet above carries the other 25. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 75% of its nominal weight, not 100%. The full arithmetic is at apis.io/rating/.

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<a href="https://apis.io/providers/furiosa/"><img src="https://apis.io/badge/furiosa/card.svg" alt="FuriosaAI on APIs.io — Kin Score by API Evangelist"></a>

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

MCP Server +12 pts — deployment.mode + probe verdict on the mcp/ manifest, not the pointer; an unprobed slug falls back to authorship
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)
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
Registration Without a Human +6 pts — a `registration_endpoint` in the served RFC 8414 / OIDC discovery document

8 more unmet checks in the Agent Readiness table above.

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

Contract Quality scores 36.3 — up to +15.9 composite points
Access Clarity scores 23.7 — up to +15.3 composite points
Operational Transparency scores 31.6 — up to +8.9 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/furiosa/apis.yml: open an issue on github.com/api-evangelist/furiosa 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)	standard	40.2	-	1
Agent Skills (SKILL.md packages)	standard	40.2	-	1
Semiconductor Consortia (RISC-V, OCP hardware, CHIPS awards)	standard	40.2	-	1
Hugging Face Hub Organisations	standard	40.2	-	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 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.

The OpenAI Interface

prose — states compatibility; nothing published to check it against

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

OpenAPI

measured — observed by APIs.io (published)

APIs 5

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

Furiosa-LLM OpenAI-Compatible Server

The HTTP server started by `furiosa-llm serve `. It hosts a single model on RNGD NPUs and exposes an OpenAI-compatible surface - /v1/completions, /v1/chat/completions, /v1/respo...

FuriosaAI Health API

The Health API from FuriosaAI — 2 operation(s) for health.

FuriosaAI Models API

The Models API from FuriosaAI — 3 operation(s) for models.

FuriosaAI Predict API

The Predict API API from FuriosaAI — 1 operation(s) for predict api.

FuriosaAI Repository API

The Repository API from FuriosaAI — 3 operation(s) for repository.

Agent Skills 3

Packaged agent skills for driving this provider's APIs from an AI assistant.

furiosa-llm-openai-client

AGENT SKILL

furiosa-run-inference

AGENT SKILL

furiosa-serve-a-model

AGENT SKILL

FuriosaAI API pricing

Pricing Plans 1

Published pricing tiers and plan structures.

Furiosa Plans Pricing

0 plans

PLANS

Rate Limits 1

Documented rate limits and quota policies.

Furiosa Rate Limits

0 limits

RATE LIMITS

FinOps 1

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

Furiosa Finops

FINOPS

Spectral Rules 1

Spectral governance rulesets for linting and validating these APIs.

FuriosaAI API Rules

29 rules · 26 errors 1 warnings 2 info

SPECTRAL

OpenAPI Overlays 2

Overlays applied on top of this provider's contracts. Each card says who wrote it: a document the provider publishes, or one API Evangelist derived or generated.

Furiosa Model Repository V2 Overlay

5 actions · update · furiosa-model-repository-v2.yaml

DERIVED

Furiosa Predict V2 Overlay

7 actions · update · furiosa-predict-v2.yaml

DERIVED

Security Posture 2

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

Furiosa Authentication

0 schemes

SECURITY

Furiosa Domain Security

TLSv1.3 · HSTS · DMARC

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

LLMsTxt

LLMsTxt

AgentSkill

AgentSkill

Design & Contract 5

Pagination, idempotency, versioning, errors, and events

Conventions

ErrorCatalog

Lifecycle

Conformance

DataModel

Build 4

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

Packages

SDKs

CLI

Access & Security 2

Authentication, authorization, and security posture

Authentication

Authentication

DomainSecurity

DomainSecurity

Operate 8

Status, limits, changes, and where to get help

Support

Community

Roadmap

ChangeLog

Contact

Deprecation

RateLimits

ChangeLog

Scroll for all 8

Commercial 3

Pricing, plans, and the legal terms of use

License

License

PrivacyPolicy

PrivacyPolicy

Plans

Plans

Company 2

The organization behind the API

Website

Website

Blog

Blog

Other 3

Properties that don't map to a standard resource type

CapabilityMap

CapabilityMap

Overlay

Overlay

Overlay

Overlay

Source (apis.yml)

aid: furiosa
name: FuriosaAI
description: 'FuriosaAI is a South Korean semiconductor company that designs data-center AI inference chips and the software
  stack that runs on them. Its second-generation NPU, RNGD, implements a Tensor Contraction Processor architecture on TSMC
  5nm and targets LLM, multi-modal and vision inference. The developer surface is software you run yourself rather than a
  hosted API: Furiosa-LLM ships an OpenAI-compatible server exposing chat, completions, responses, embeddings, score, rerank,
  models, tokenizer and Prometheus metrics endpoints, and the earlier Furiosa Model Server implements the KServe v2 Predict
  Protocol and the Triton Model Repository extension over REST and gRPC. Around that sit Python, Go and Rust packages, a furiosa-smi
  device CLI, container images, an APT/RPM package repository, and a Kubernetes cloud-native toolkit (device plugin, DRA driver,
  feature discovery, metrics exporter, NPU operator).'
url: https://raw.githubusercontent.com/api-evangelist/furiosa/refs/heads/main/apis.yml
x-type: company
x-source: harvest:secondary-market
deliveryModel:
  model: unknown
  open_source: unknown
  commercial: true
  callable_host: false
  label: Delivery model not determined — needs a product licence on record
  confidence: low
  source:
  - openapi
  - pricing
  - repository-unlicensed
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: unknown
  onboarding: approval
  trial: false
  try_now: false
  public: false
  label: Requires approval
  confidence: medium
  source:
  - plans
  - authentication
  - rate-limits
  - security
  - sandbox
  generated: '2026-11-06'
  method: derived
specificationVersion: '0.23'
created: '2026-08-16'
modified: '2026-08-16'
image: https://furiosa.ai/favicon.ico
tags:
- Artificial Intelligence
- Machine Learning
- Inference
- Semiconductors
- NPU
- Hardware
- LLM
- Model Serving
- Kubernetes
- Developer Tools
- Compute
- Infrastructure
tags_raw:
- Artificial Intelligence
- Machine Learning
- Inference
- Semiconductors
- NPU
- Hardware
- LLM
- Model Serving
- Kubernetes
- Developer Tools
- Compute
- Infrastructure
- Machine-Learning
apis:
- aid: furiosa:furiosa-llm-openai-server
  name: Furiosa-LLM OpenAI-Compatible Server
  description: The HTTP server started by `furiosa-llm serve <ARTIFACT_PATH>`. It hosts a single model on RNGD NPUs and exposes
    an OpenAI-compatible surface - /v1/completions, /v1/chat/completions, /v1/responses (OpenResponses), /v1/embeddings, /v1/models,
    /v1/models/{model_id} - plus the vLLM-originated /score and /rerank pooling endpoints, a tokenizer API (/tokenize, /detokenize,
    /tokenizer_info), GET /version and a Prometheus GET /metrics endpoint. It is customer-hosted software, so the base URL
    below is templated on the operator's own host; the documented default is http://localhost:8000/v1. FuriosaAI publishes
    no OpenAPI for this surface - the parameter tables in the serving docs are the contract.
  humanURL: https://developer.furiosa.ai/latest/en/furiosa_llm/furiosa-llm-serve.html
  baseURL: http://{furiosa_llm_host}:8000/v1
  tags:
  - LLM
  - Inference
  - OpenAI-Compatible
  tags_raw:
  - LLM
  - Inference
  - OpenAI Compatible
  properties:
  - type: Documentation
    url: https://developer.furiosa.ai/latest/en/furiosa_llm/furiosa-llm-serve.html
  - type: APIReference
    url: https://developer.furiosa.ai/latest/en/furiosa_llm/reference.html
  - type: Authentication
    url: authentication/furiosa-authentication.yml
  - type: Conventions
    url: conventions/furiosa-conventions.yml
  - type: RateLimits
    url: rate-limits/furiosa-rate-limits.yml
- aid: furiosa:furiosa-health-api
  name: FuriosaAI Health API
  description: The Health API from FuriosaAI — 2 operation(s) for health.
  humanURL: https://developer.furiosa.ai/latest/en/furiosa_llm/furiosa-llm-serve.html
  baseURL: http://{furiosa_llm_host}:8000/v1
  tags:
  - Health
  properties:
  - type: OpenAPI
    url: openapi/furiosa-health-api-openapi.yml
  - type: Protobuf
    url: grpc/furiosa-predict.proto
  - type: ErrorCatalog
    url: errors/furiosa-problem-types.yml
  - type: DataModel
    url: data-model/furiosa-data-model.yml
  - type: SourceCode
    url: https://github.com/furiosa-ai/furiosa-sdk
  - type: Protobuf
    url: grpc/furiosa-model-repository.proto
- aid: furiosa:furiosa-models-api
  name: FuriosaAI Models API
  description: The Models API from FuriosaAI — 3 operation(s) for models.
  humanURL: https://developer.furiosa.ai/latest/en/furiosa_llm/furiosa-llm-serve.html
  baseURL: http://{furiosa_llm_host}:8000/v1
  tags:
  - Models
  properties:
  - type: OpenAPI
    url: openapi/furiosa-models-api-openapi.yml
  - type: Protobuf
    url: grpc/furiosa-predict.proto
  - type: ErrorCatalog
    url: errors/furiosa-problem-types.yml
  - type: DataModel
    url: data-model/furiosa-data-model.yml
  - type: SourceCode
    url: https://github.com/furiosa-ai/furiosa-sdk
  - type: Protobuf
    url: grpc/furiosa-model-repository.proto
- aid: furiosa:furiosa-predict-api-api
  name: FuriosaAI Predict API
  description: The Predict API API from FuriosaAI — 1 operation(s) for predict api.
  humanURL: https://developer.furiosa.ai/latest/en/furiosa_llm/furiosa-llm-serve.html
  baseURL: http://{furiosa_llm_host}:8000/v1
  tags:
  - Predict API
  properties:
  - type: OpenAPI
    url: openapi/furiosa-predict-api-api-openapi.yml
  - type: Protobuf
    url: grpc/furiosa-predict.proto
  - type: ErrorCatalog
    url: errors/furiosa-problem-types.yml
  - type: DataModel
    url: data-model/furiosa-data-model.yml
  - type: SourceCode
    url: https://github.com/furiosa-ai/furiosa-sdk
  - type: Protobuf
    url: grpc/furiosa-model-repository.proto
- aid: furiosa:furiosa-repository-api
  name: FuriosaAI Repository API
  description: The Repository API from FuriosaAI — 3 operation(s) for repository.
  humanURL: https://developer.furiosa.ai/latest/en/furiosa_llm/furiosa-llm-serve.html
  baseURL: http://{furiosa_llm_host}:8000/v1
  tags:
  - Repository
  properties:
  - type: OpenAPI
    url: openapi/furiosa-repository-api-openapi.yml
  - type: Protobuf
    url: grpc/furiosa-predict.proto
  - type: ErrorCatalog
    url: errors/furiosa-problem-types.yml
  - type: DataModel
    url: data-model/furiosa-data-model.yml
  - type: SourceCode
    url: https://github.com/furiosa-ai/furiosa-sdk
  - type: Protobuf
    url: grpc/furiosa-model-repository.proto
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: CapabilityMap
  url: capabilities/furiosa-capability-edges.yml
  name: FuriosaAI Business Capability Map
- type: License
  name: Apache-2.0
  url: https://github.com/furiosa-ai/furiosa-sdk/blob/main/LICENSE
- type: Overlay
  url: overlays/furiosa-predict-v2-overlay.yaml
- type: Overlay
  url: overlays/furiosa-model-repository-v2-overlay.yaml
- type: Website
  url: https://furiosa.ai/
- type: DeveloperPortal
  url: https://developer.furiosa.ai/latest/en/
- type: Documentation
  url: https://developer.furiosa.ai/latest/en/
- type: APIReference
  url: https://developer.furiosa.ai/latest/en/furiosa_llm/reference.html
- type: GettingStarted
  url: https://developer.furiosa.ai/latest/en/get_started/furiosa_llm.html
- type: Support
  url: https://furiosa-ai.atlassian.net/servicedesk/customer/portals
- type: Community
  url: https://forums.furiosa.ai/
- type: Blog
  url: https://furiosa.ai/blog
- type: GitHubOrganization
  url: https://github.com/furiosa-ai
- type: Roadmap
  url: https://developer.furiosa.ai/latest/en/overview/roadmap.html
- type: ChangeLog
  url: https://developer.furiosa.ai/latest/en/whatsnew/index.html
- type: SignUp
  url: https://lp.furiosa.ai/furiosa-access-program
- type: PrivacyPolicy
  url: https://furiosa.ai/privacy-policy
- type: Contact
  url: https://furiosa.ai/contact
- type: Packages
  url: packages/furiosa-packages.yml
- type: SDKs
  url: packages/furiosa-packages.yml
- type: CLI
  url: cli/furiosa-cli.yml
- type: Sandbox
  url: sandbox/furiosa-sandbox.yml
- type: Authentication
  url: authentication/furiosa-authentication.yml
- type: Conventions
  url: conventions/furiosa-conventions.yml
- type: ErrorCatalog
  url: errors/furiosa-problem-types.yml
- type: Lifecycle
  url: lifecycle/furiosa-lifecycle.yml
- type: Deprecation
  url: lifecycle/furiosa-lifecycle.yml
- type: Conformance
  url: conformance/furiosa-conformance.yml
- type: DataModel
  url: data-model/furiosa-data-model.yml
- type: DomainSecurity
  url: security/furiosa-domain-security.yml
- type: LLMsTxt
  url: llms/furiosa-llms.txt
- type: AgentSkill
  url: skills/_index.yml
- type: Plans
  url: plans/furiosa-plans-pricing.yml
- type: RateLimits
  url: rate-limits/furiosa-rate-limits.yml
- type: ChangeLog
  url: changelog/furiosa-changelog.yml
x-enrichment:
  date: '2026-08-16'
  status: enriched
  artifacts_added: 26
  pass: local-v1
x-base-url-note: All three baseURL values are TEMPLATED on purpose, not missing. FuriosaAI operates no hosted API; both HTTP
  surfaces are servers the customer starts on their own machine. The published defaults are http://localhost:8000/v1 for `furiosa-llm
  serve` and ports 8080 (REST) / 8081 (gRPC) for furiosa-server. repair-api-bases.py reports `no-usable-base` for this repo,
  which is the correct and expected reading of a self-hosted product rather than a defect to repair.
x-contract-discovery:
  date: '2026-08-16'
  openapi_on_api_hosts: /openapi.json, /openapi.yaml, /swagger.json and /api-docs all returned 404 on furiosa.ai and developer.furiosa.ai;
    api.furiosa.ai and docs.furiosa.ai do not resolve. The two OpenAPI documents in this repo were found instead in FuriosaAI's
    own GitHub repository at furiosa-ai/furiosa-sdk/python/furiosa-server/openapi/.
  ownership_note: 'Ownership check on those two specs. Their info.title reads "Predict API" and "Model Repository" and info.description
    points at kubeflow/kfserving and triton-inference-server rather than at FuriosaAI, and servers[] is empty. They are nonetheless
    FuriosaAI''s published contract: the furiosa-server README in the same first-party repository states the server is "compliant
    with KFServing''s V2 Dataplane specification and Triton''s Model Repository specification" and lists "OpenAPI specification
    support" as a shipped feature, so the specs describe FuriosaAI''s own product implementing a borrowed protocol verbatim
    - the same reason the .proto files carry upstream provenance headers.'
  graphql: No GraphQL surface exists or is documented.
  mcp: No MCP server, hosted or stdio, in 158 public repos or any registry. The developer center's only MCP mention is negative
    - the Responses API page states mcp built-in tools are not supported.
  a2a: /.well-known/agent-card.json and /.well-known/agent.json returned 404 on all three hosts.
  llms_txt: /llms.txt returned 404 on furiosa.ai and developer.furiosa.ai.

FuriosaAI API — frequently asked questions

Does FuriosaAI have an API?

Yes. APIs.io lists 5 APIs from FuriosaAI, including Furiosa-LLM OpenAI-Compatible Server, FuriosaAI Health API and FuriosaAI Models API, and 2 more.

Is there an OpenAPI specification for the FuriosaAI API?

Yes. APIs.io indexes 4 OpenAPI specifications for FuriosaAI, each linked for download from this page.

How do I authenticate with the FuriosaAI API?

FuriosaAI uses bearer-token authentication (0 schemes). The details are profiled on APIs.io as Furiosa Authentication.

Is the FuriosaAI API ready for AI agents?

FuriosaAI has a Kin Score of 45.0 out of 100 (developing) and an Agent Readiness score of 21.3 (agent-aware), scored by API Evangelist on 2026-11-06.

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