Qubrid AI

Qubrid AI is a cloud platform that provides GPU-accelerated infrastructure and AI services for enterprise developers. Their developer platform offers OpenAI-compatible inference endpoints, GPU compute provisioning, model fine-tuning, and retrieval-augmented generation capabilities, all running on NVIDIA GPU infrastructure.

Qubrid AI publishes 13 API contracts indexed on the APIs.io network, including Chat Completions API, Datasets API, Documents API, and 10 more. Tagged areas include Artificial Intelligence, Cloud Computing, GPU, Inference, and LLM.

The Qubrid AI catalog on APIs.io includes 1 JSON-LD context and 1 Spectral governance ruleset.

Qubrid AI’s developer surface includes engineering blog, pricing, authentication, developer portal, documentation, and 12 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

41.6/100 developing ▬ flat Agent 26/100 agent aware Front door AI 6/6 dominant Heartbeat 31/100 slowing saas Full breakdown ↓
scored 2026-11-06 · rubric v0.27.0 · Show this score on your site →

AccessPaid

4 published contracts

Artificial Intelligence Cloud Computing GPU Inference LLM Machine Learning NVIDIA Serverless

What this lets a business do 3

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

AI Model Services

AE-110

DocumentsEmbeddingsKnowledge BasesModelsRAG Queries

POST /embeddings POST /rag/query POST /rag/knowledge-bases/{knowledge_base_id}/documents POST /rag/knowledge-bases

Information & Data Management

BC-610

Chat CompletionsDatasetsFine-Tuned ModelsFine-Tuning Jobs

POST /fine-tuning/jobs GET /fine-tuning/models POST /chat/completions GET /fine-tuning/datasets

Information Technology Management

BC-600

Instances

POST /instances

Kin Score

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

Composite quality — 41.6/100 · developing

Contract Quality 11.5 / 19

Developer Ergonomics 5.0 / 15

Access Clarity 7.7 / 15

Operational Transparency 0.8 / 10

Contract Governance 0.9 / 9

Discoverability 5.9 / 8

Regulatory Posture 2.3 / 15

Create-or-Update Ergonomics 0.0 / 10

Agent readiness — 26/100 · agent aware

Machine-Readable Contract 18 / 18

Agentic Access Contract 10 / 10

Documented Reversibility 6 / 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 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 0 / 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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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
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
Delegated User Identity +6 pts — a served discovery document listing authorization_code in grant_types_supported (served), else an oauth2 authorizationCode flow or openIdConnect declared in an OpenAPI (documented)

8 more unmet checks in the Agent Readiness table above.

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

Developer Ergonomics scores 33.3 — up to +13.3 composite points
Operational Transparency scores 7.9 — up to +12.0 composite points
Contract Governance scores 9.8 — up to +10.8 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/qubrid-ai/apis.yml: open an issue on github.com/api-evangelist/qubrid-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 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 reaches extended

declared — publishes a spec that declares them

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

OpenAPI

measured — observed by APIs.io (published)

APIs 13

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

Qubrid AI Chat Completions API

Generate chat-based completions using open-source large language models hosted on NVIDIA GPU infrastructure. Compatible with the OpenAI chat completions request and response for...

Qubrid AI Datasets API

Upload and manage CSV training datasets used for fine-tuning models. Datasets must be in CSV format with columns appropriate for the selected task type (QA or non-QA).

Qubrid AI Documents API

Upload, list, and manage documents within a knowledge base. Supported formats include PDF, text, CSV, and other common document types. Documents are automatically processed, chu...

Qubrid AI Embeddings API

Generate vector embeddings from text input using embedding models hosted on the Qubrid AI platform, suitable for semantic search, clustering, and retrieval-augmented generation ...

Qubrid AI Fine-Tuning Jobs API

Create, monitor, and manage fine-tuning jobs that customize pre-deployed text generation and code generation models using uploaded training datasets on GPU infrastructure.

Qubrid AI GPU Catalog API

Browse available GPU types, configurations, and pricing tiers including on-demand, weekly, monthly, and reserved options for NVIDIA, AMD, and Intel accelerators.

Qubrid AI Instances API

Provision, manage, start, stop, and terminate GPU compute instances on the Qubrid AI platform. Instances include NVIDIA H100, H200, and B200 accelerators with configurable memor...

Qubrid AI Knowledge Bases API

Create and manage knowledge bases that store enterprise and departmental data for retrieval-augmented generation. Each knowledge base contains ingested documents that are chunke...

Qubrid AI Models API

List and retrieve details about the open-source AI models available for inference on the Qubrid AI platform, including text generation, code generation, vision-language, and ima...

Qubrid AI RAG Queries API

Query a knowledge base using natural language with retrieval-augmented generation. The API retrieves relevant document chunks from the knowledge base and uses them as context fo...

Qubrid AI SSH Keys API

Manage SSH keys for secure access to GPU compute instances. Users get full root access to their instances for installing custom libraries, running scripts, and managing workloads.

Qubrid AI Templates API

List and deploy pre-configured AI and ML environment templates including PyTorch, TensorFlow, ComfyUI, n8n, and Langflow, all optimized to run on Qubrid GPU instances.

Qubrid AI Finetuned Models API

List and manage fine-tuned model artifacts produced by completed fine-tuning jobs. Fine-tuned models can be deployed for inference on the Qubrid AI platform.

Scroll for all 13

Open Collections 17

Open, tool-agnostic API collections (OpenAPI-derived and Bruno).

Qubrid AI Compute Chat Completions API

OPEN COLLECTION

Qubrid AI Compute API

OPEN COLLECTION

Qubrid AI Compute Chat Completions Datasets API

OPEN COLLECTION

Qubrid AI Compute Chat Completions Documents API

OPEN COLLECTION

Qubrid AI Compute Chat Completions Embeddings API

OPEN COLLECTION

Qubrid AI Compute Chat Completions Fine-Tuned Models API

OPEN COLLECTION

Qubrid AI Compute Chat Completions Fine-Tuning Jobs API

OPEN COLLECTION

Qubrid AI Fine-Tuning API

OPEN COLLECTION

Qubrid AI Compute Chat Completions GPU Catalog API

OPEN COLLECTION

Qubrid AI Inference API

OPEN COLLECTION

Qubrid AI Compute Chat Completions Instances API

OPEN COLLECTION

Qubrid AI Compute Chat Completions Knowledge Bases API

OPEN COLLECTION

Qubrid AI Compute Chat Completions Models API

OPEN COLLECTION

Qubrid AI Compute Chat Completions RAG Queries API

OPEN COLLECTION

Qubrid AI RAG API

OPEN COLLECTION

Qubrid AI Compute Chat Completions SSH Keys API

OPEN COLLECTION

Qubrid AI Compute Chat Completions Templates API

OPEN COLLECTION

Scroll for all 17

Qubrid AI API pricing

Prices published by Qubrid AI, read 2026-09-20 from qubrid.com/pricing.

Plan	Price
NVIDIA B300 288GB 8-GPU Bare Metal Server	$389,400 Includes: GPU: 8 x NVIDIA B300 288GB HGX SXM GPU; CPU: 2 x 48 Cores 2.3GHz; ~3 TB DDR5; 1 x 1.9 TB M.2 NVMe bo
NVIDIA B200 180GB 8-GPU SXM Server	$297,840 Includes: GPU: 8 x NVIDIA B200 180GB HGX SXM GPU; 32 x 96GB DDR4-5600; 2 x 960GB NVMe M.2; 4 x 7.68TB NVMe
NVIDIA H200 141GB 8-GPU SXM Server	$210,240 Includes: GPU: 8 x NVIDIA H200 HGX 141GB SXM; 32 x 64GB DDR5-5600; 2 x 960GB NVMe M.2; 8 x 3.8TB NVMe
NVIDIA H100 80GB 8-GPU SXM Server	$133,414.80 Includes: GPU: 8 x NVIDIA H100 80GB HGX SXM; 16 x 64GB DDR5-5600; 2 x 480GB NVMe M.2; 6 x 3.84TB NVMe
NVIDIA A100 80GB 8-GPU SXM Server	$89,500 Includes: GPU: 8 x NVIDIA A100 80GB HGX SXM; 16 x 64GB DDR4-3200; 2 x 960GB NVMe M.2; 2 x 1.9TB NVMe

Plan details, limits and sources →

Rate limits

Inference Rate Limit: see Qubrid platform console varies
GPU Provisioning Quota: see Qubrid platform console varies

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

Billed by: server · FinOps profile →

Pricing Plans 2

Published pricing tiers and plan structures.

Qubrid Ai Plans Pricing

5 plans

PLANS

Qubrid Ai Price Estimates

0 plans

PLANS

Rate Limits 1

Documented rate limits and quota policies.

Qubrid Ai Rate Limits

2 limits

RATE LIMITS

Service Levels 1

Uptime the provider promises or reports, as SLA4OAI. Read from its own pages; APIs.io runs no monitors.

Qubrid AI

SLA

FinOps 1

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

Qubrid Ai Finops

FINOPS

Semantic Vocabularies 1

JSON-LD contexts and semantic vocabularies used across these APIs.

Qubrid Ai Context

0 classes · 8 properties

JSON-LD

Spectral Rules 1

Spectral governance rulesets for linting and validating these APIs.

Qubrid AI — jsonschema rules

6 rules · 5 warnings 1 info

SPECTRAL

JSON Schema 4

Standalone JSON Schema definitions for this provider's data models.

Qubrid AI Compute Entities

0 properties

JSON SCHEMA

Qubrid AI Fine-Tuning Entities

0 properties

JSON SCHEMA

Qubrid AI Inference Entities

0 properties

JSON SCHEMA

Qubrid AI RAG Entities

0 properties

JSON SCHEMA

Security Posture 2

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

Qubrid Ai Authentication

http · 1 scheme

SECURITY

Qubrid Ai Domain Security

TLSv1.2 · DMARC

SECURITY

Agentic Access 1

Recommended x-agentic-access execution contracts for AI agents.

Qubrid Ai Agentic Access

33 operations · 17 acting · 2 human-in-the-loop

33 operations · 17 acting

AGENTIC

Resources

Get Started 2

Portal, sign-up, and the first successful call

Portal

Portal

Login

Documentation 1

Reference material describing how the API behaves

Documentation

Documentation

Agent Surfaces 2

MCP servers, agent skills, and machine-readable catalogs

AgenticAccess

AgenticAccess

LlmsText

LlmsText

Design & Contract 1

Pagination, idempotency, versioning, errors, and events

JSONLD

JSONLD

Build 1

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

GitHubOrganization

Access & Security 2

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Authentication

Authentication

Operate 1

Status, limits, changes, and where to get help

RateLimits

RateLimits

Commercial 3

Pricing, plans, and the legal terms of use

FinOps

FinOps

Pricing

Pricing

Plans

Plans

Company 3

The organization behind the API

Blog

Blog

LinkedIn

Website

Website

Other 1

Properties that don't map to a standard resource type

CapabilityMap

CapabilityMap

Source (apis.yml)

aid: qubrid-ai
name: Qubrid AI
description: Qubrid AI is a cloud platform that provides GPU-accelerated infrastructure and AI services for enterprise developers.
  Their developer platform offers OpenAI-compatible inference endpoints, GPU compute provisioning, model fine-tuning, and
  retrieval-augmented generation capabilities, all running on NVIDIA GPU infrastructure.
kind: contract
deliveryModel:
  model: saas
  open_source: false
  commercial: true
  callable_host: true
  label: Hosted service · you call their endpoint
  confidence: high
  source:
  - openapi
  - pricing
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: paid
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Paid
  confidence: medium
  source:
  - plans
  - authentication
  - security
  generated: '2026-11-06'
  method: derived
position: Consuming
access: 3rd-Party
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/qubrid-ai.png
tags:
- Artificial Intelligence
- Cloud Computing
- GPU
- Inference
- LLM
- Machine Learning
- NVIDIA
- Serverless
tags_raw:
- Artificial Intelligence
- Cloud Computing
- GPU
- Inference
- Large Language Models
- Machine Learning
- NVIDIA
- Serverless
- Machine-Learning
url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/apis.yml
created: '2026-03-24'
modified: '2026-10-06'
specificationVersion: '0.23'
apis:
- aid: qubrid-ai:qubrid-ai-chat-completions-api
  name: Qubrid AI Chat Completions API
  description: Generate chat-based completions using open-source large language models hosted on NVIDIA GPU infrastructure.
    Compatible with the OpenAI chat completions request and response format.
  humanURL: https://docs.platform.qubrid.com
  baseURL: https://platform.qubrid.com/api/v1
  tags:
  - Chat Completions
  properties:
  - type: OpenAPI
    url: openapi/qubrid-ai-chat-completions-api-openapi.yml
  - type: Documentation
    url: https://docs.platform.qubrid.com
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-inference-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-compute-schema.json
  - type: Documentation
    url: https://docs.platform.qubrid.com/Fine%20Tuning
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-fine-tuning-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-rag-schema.json
- aid: qubrid-ai:qubrid-ai-datasets-api
  name: Qubrid AI Datasets API
  description: Upload and manage CSV training datasets used for fine-tuning models. Datasets must be in CSV format with columns
    appropriate for the selected task type (QA or non-QA).
  humanURL: https://docs.platform.qubrid.com
  baseURL: https://platform.qubrid.com/api/v1
  tags:
  - Datasets
  properties:
  - type: OpenAPI
    url: openapi/qubrid-ai-datasets-api-openapi.yml
  - type: Documentation
    url: https://docs.platform.qubrid.com
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-inference-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-compute-schema.json
  - type: Documentation
    url: https://docs.platform.qubrid.com/Fine%20Tuning
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-fine-tuning-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-rag-schema.json
- aid: qubrid-ai:qubrid-ai-documents-api
  name: Qubrid AI Documents API
  description: Upload, list, and manage documents within a knowledge base. Supported formats include PDF, text, CSV, and other
    common document types. Documents are automatically processed, chunked, and embedded upon upload.
  humanURL: https://docs.platform.qubrid.com
  baseURL: https://platform.qubrid.com/api/v1
  tags:
  - Documents
  properties:
  - type: OpenAPI
    url: openapi/qubrid-ai-documents-api-openapi.yml
  - type: Documentation
    url: https://docs.platform.qubrid.com
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-inference-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-compute-schema.json
  - type: Documentation
    url: https://docs.platform.qubrid.com/Fine%20Tuning
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-fine-tuning-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-rag-schema.json
- aid: qubrid-ai:qubrid-ai-embeddings-api
  name: Qubrid AI Embeddings API
  description: Generate vector embeddings from text input using embedding models hosted on the Qubrid AI platform, suitable
    for semantic search, clustering, and retrieval-augmented generation workflows.
  humanURL: https://docs.platform.qubrid.com
  baseURL: https://platform.qubrid.com/api/v1
  tags:
  - Embeddings
  properties:
  - type: OpenAPI
    url: openapi/qubrid-ai-embeddings-api-openapi.yml
  - type: Documentation
    url: https://docs.platform.qubrid.com
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-inference-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-compute-schema.json
  - type: Documentation
    url: https://docs.platform.qubrid.com/Fine%20Tuning
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-fine-tuning-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-rag-schema.json
- aid: qubrid-ai:qubrid-ai-fine-tuning-jobs-api
  name: Qubrid AI Fine-Tuning Jobs API
  description: Create, monitor, and manage fine-tuning jobs that customize pre-deployed text generation and code generation
    models using uploaded training datasets on GPU infrastructure.
  humanURL: https://docs.platform.qubrid.com
  baseURL: https://platform.qubrid.com/api/v1
  tags:
  - Fine-Tuning Jobs
  properties:
  - type: OpenAPI
    url: openapi/qubrid-ai-fine-tuning-jobs-api-openapi.yml
  - type: Documentation
    url: https://docs.platform.qubrid.com
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-inference-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-compute-schema.json
  - type: Documentation
    url: https://docs.platform.qubrid.com/Fine%20Tuning
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-fine-tuning-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-rag-schema.json
- aid: qubrid-ai:qubrid-ai-gpu-catalog-api
  name: Qubrid AI GPU Catalog API
  description: Browse available GPU types, configurations, and pricing tiers including on-demand, weekly, monthly, and reserved
    options for NVIDIA, AMD, and Intel accelerators.
  humanURL: https://docs.platform.qubrid.com
  baseURL: https://platform.qubrid.com/api/v1
  tags:
  - GPU Catalog
  properties:
  - type: OpenAPI
    url: openapi/qubrid-ai-gpu-catalog-api-openapi.yml
  - type: Documentation
    url: https://docs.platform.qubrid.com
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-inference-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-compute-schema.json
  - type: Documentation
    url: https://docs.platform.qubrid.com/Fine%20Tuning
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-fine-tuning-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-rag-schema.json
- aid: qubrid-ai:qubrid-ai-instances-api
  name: Qubrid AI Instances API
  description: Provision, manage, start, stop, and terminate GPU compute instances on the Qubrid AI platform. Instances include
    NVIDIA H100, H200, and B200 accelerators with configurable memory, storage, and networking.
  humanURL: https://docs.platform.qubrid.com
  baseURL: https://platform.qubrid.com/api/v1
  tags:
  - Instances
  properties:
  - type: OpenAPI
    url: openapi/qubrid-ai-instances-api-openapi.yml
  - type: Documentation
    url: https://docs.platform.qubrid.com
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-inference-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-compute-schema.json
  - type: Documentation
    url: https://docs.platform.qubrid.com/Fine%20Tuning
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-fine-tuning-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-rag-schema.json
- aid: qubrid-ai:qubrid-ai-knowledge-bases-api
  name: Qubrid AI Knowledge Bases API
  description: Create and manage knowledge bases that store enterprise and departmental data for retrieval-augmented generation.
    Each knowledge base contains ingested documents that are chunked, embedded, and stored in a vector database for semantic
    search during inference.
  humanURL: https://docs.platform.qubrid.com
  baseURL: https://platform.qubrid.com/api/v1
  tags:
  - Knowledge Bases
  properties:
  - type: OpenAPI
    url: openapi/qubrid-ai-knowledge-bases-api-openapi.yml
  - type: Documentation
    url: https://docs.platform.qubrid.com
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-inference-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-compute-schema.json
  - type: Documentation
    url: https://docs.platform.qubrid.com/Fine%20Tuning
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-fine-tuning-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-rag-schema.json
- aid: qubrid-ai:qubrid-ai-models-api
  name: Qubrid AI Models API
  description: List and retrieve details about the open-source AI models available for inference on the Qubrid AI platform,
    including text generation, code generation, vision-language, and image generation models.
  humanURL: https://docs.platform.qubrid.com
  baseURL: https://platform.qubrid.com/api/v1
  tags:
  - Models
  properties:
  - type: OpenAPI
    url: openapi/qubrid-ai-models-api-openapi.yml
  - type: Documentation
    url: https://docs.platform.qubrid.com
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-inference-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-compute-schema.json
  - type: Documentation
    url: https://docs.platform.qubrid.com/Fine%20Tuning
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-fine-tuning-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-rag-schema.json
- aid: qubrid-ai:qubrid-ai-rag-queries-api
  name: Qubrid AI RAG Queries API
  description: Query a knowledge base using natural language with retrieval-augmented generation. The API retrieves relevant
    document chunks from the knowledge base and uses them as context for generating accurate, grounded responses through a
    large language model.
  humanURL: https://docs.platform.qubrid.com
  baseURL: https://platform.qubrid.com/api/v1
  tags:
  - RAG Queries
  properties:
  - type: OpenAPI
    url: openapi/qubrid-ai-rag-queries-api-openapi.yml
  - type: Documentation
    url: https://docs.platform.qubrid.com
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-inference-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-compute-schema.json
  - type: Documentation
    url: https://docs.platform.qubrid.com/Fine%20Tuning
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-fine-tuning-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-rag-schema.json
- aid: qubrid-ai:qubrid-ai-ssh-keys-api
  name: Qubrid AI SSH Keys API
  description: Manage SSH keys for secure access to GPU compute instances. Users get full root access to their instances for
    installing custom libraries, running scripts, and managing workloads.
  humanURL: https://docs.platform.qubrid.com
  baseURL: https://platform.qubrid.com/api/v1
  tags:
  - SSH Keys
  properties:
  - type: OpenAPI
    url: openapi/qubrid-ai-ssh-keys-api-openapi.yml
  - type: Documentation
    url: https://docs.platform.qubrid.com
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-inference-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-compute-schema.json
  - type: Documentation
    url: https://docs.platform.qubrid.com/Fine%20Tuning
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-fine-tuning-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-rag-schema.json
- aid: qubrid-ai:qubrid-ai-templates-api
  name: Qubrid AI Templates API
  description: List and deploy pre-configured AI and ML environment templates including PyTorch, TensorFlow, ComfyUI, n8n,
    and Langflow, all optimized to run on Qubrid GPU instances.
  humanURL: https://docs.platform.qubrid.com
  baseURL: https://platform.qubrid.com/api/v1
  tags:
  - Templates
  properties:
  - type: OpenAPI
    url: openapi/qubrid-ai-templates-api-openapi.yml
  - type: Documentation
    url: https://docs.platform.qubrid.com
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-inference-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-compute-schema.json
  - type: Documentation
    url: https://docs.platform.qubrid.com/Fine%20Tuning
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-fine-tuning-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-rag-schema.json
- aid: qubrid-ai:qubrid-ai-finetuned-models-api
  name: Qubrid AI Finetuned Models API
  description: List and manage fine-tuned model artifacts produced by completed fine-tuning jobs. Fine-tuned models can be
    deployed for inference on the Qubrid AI platform.
  humanURL: https://docs.platform.qubrid.com
  baseURL: https://platform.qubrid.com/api/v1
  tags:
  - Fine-Tuned Models
  tags_raw:
  - Finetuned Models
  properties:
  - type: OpenAPI
    url: openapi/qubrid-ai-finetuned-models-api-openapi.yml
  - type: Documentation
    url: https://docs.platform.qubrid.com
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-inference-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-compute-schema.json
  - type: Documentation
    url: https://docs.platform.qubrid.com/Fine%20Tuning
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-fine-tuning-schema.json
  - type: JSONSchema
    url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-schema/qubrid-ai-rag-schema.json
common:
- type: RateLimits
  url: rate-limits/qubrid-ai-rate-limits.yml
- type: FinOps
  url: finops/qubrid-ai-finops.yml
- url: https://qubrid.com/blog/
  type: Blog
- type: Pricing
  url: https://qubrid.com/pricing
- type: Plans
  url: plans/qubrid-ai-plans-pricing.yml
- type: CapabilityMap
  url: capabilities/qubrid-ai-capability-edges.yml
  name: Qubrid AI Business Capability Map
- type: AgenticAccess
  url: agentic-access/qubrid-ai-agentic-access.yml
- type: DomainSecurity
  url: security/qubrid-ai-domain-security.yml
- type: Authentication
  url: authentication/qubrid-ai-authentication.yml
- type: GitHubOrganization
  url: https://github.com/QubridAI-Inc
- type: LinkedIn
  url: https://www.linkedin.com/company/qubrid
- type: Portal
  url: https://platform.qubrid.com
- type: Documentation
  url: https://docs.platform.qubrid.com
- type: Website
  url: https://qubrid.com
- type: Login
  url: https://platform.qubrid.com/login
- type: JSONLD
  url: https://raw.githubusercontent.com/api-evangelist/qubrid-ai/refs/heads/main/json-ld/qubrid-ai-context.jsonld
- type: Integrations
  url: https://qubrid.com/partners
- type: LlmsText
  url: https://docs.platform.qubrid.com/llms.txt
integrations:
- name: Qubrid AI
- name: Scribble
- name: NVIDIA
- name: SuperMCR
- name: Hewlett Packard Enterprise
- name: Dell
- name: Lenovo
- name: AWS
- name: Oracle
- name: GCP
- name: Alibaba
- name: Intel
- name: AMD
- name: Cisco
- name: LinkedIn
- name: Reddit
- name: GitHub
- name: Discord
- name: YouTube
maintainers:
- FN: API Evangelist
  email: info@apievangelist.com

Qubrid AI API — frequently asked questions

Does Qubrid AI have an API?

Yes. APIs.io lists 13 APIs from Qubrid AI, including Qubrid AI Chat Completions API, Qubrid AI Datasets API and Qubrid AI Documents API, and 10 more.

Is there an OpenAPI specification for the Qubrid AI API?

Yes. APIs.io indexes 13 OpenAPI specifications for Qubrid AI, each linked for download from this page.

How do I authenticate with the Qubrid AI API?

Qubrid AI uses bearer-token authentication (http · 1 scheme). The details are profiled on APIs.io as Qubrid Ai Authentication.

How much does the Qubrid AI API cost?

Qubrid AI publishes its prices; its NVIDIA B300 288GB 8-GPU Bare Metal Server plan is $389,400 as of 2026-09-20. APIs.io lists 5 pricing plans for Qubrid AI, with each plan's price, limits and inclusions under Pricing on this page.

Is the Qubrid AI API ready for AI agents?

Qubrid AI has a Kin Score of 41.6 out of 100 (developing) and an Agent Readiness score of 26.0 (agent-aware), scored by API Evangelist on 2026-11-06.

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