use-case

Model originators, hosted clouds, aggregators, and local runtimes

Direct answerA provider guide answers who develops the model; a channel answers where a request is routed. The same model through another host can change authentication, protocol, region, version, and data boundary.

Updated · Reviewed

Beginner: who built it versus where it is called

An originator defines weights, capability, and lifecycle. A hosted cloud offers third-party models in its regions and identity system. An aggregator exposes several suppliers through a common protocol. A workflow platform exposes an application or knowledge base. A local runtime loads models on owned hardware. An account bridge converts another identity system into access. All may appear in channel configuration, but they are not all model vendors.

Six integration shapes

TypeExamplesVerify
OriginatorOpenAI, Anthropic, Google, DeepSeekOfficial ID, native protocol, retirement
Hosted cloudAWS Bedrock, Azure AI Foundry, Vertex AIRegion, deployment name, platform version, origin
AggregatorOpenRouter, SiliconFlow, ReplicateEffective supplier, routing, protocol subset
WorkflowDify, Coze, FastGPTApp ID, conversation state, knowledge semantics
Local runtimeOllama, XinferenceArtifact, license, hardware, network exposure
Account bridgeOAuth or account-based accessIdentity, scopes, session, service terms

Minimal verification

Query /v1/models with the site token, then inspect the marketplace for exact ID, enabled endpoint, and price. A platform name inside an ID does not establish model authorship, and a platform catalog does not guarantee every region, account, or endpoint.

A channel switch is not a base-URL edit

Retest authentication, model or deployment name, fields, tool schema, stream events, errors, usage, media delivery, and limits. A host may pin an older snapshot, an aggregator may fail over among suppliers, and a local runtime changes with quantization, templates, and hardware.

Data and compliance boundary

Retain the channel and originator for every request. Determine which entities process data, in which region, for how long, and for what abuse monitoring. Automatic failover can change that boundary. A zero-retention requirement cannot rely on a model name or a platform-wide slogan.

Expert routing governance

Give every channel a capability allowlist, health score, cost, latency, data class, and failover policy. Do not fail over every error: validation, permission, balance, and policy failures rarely improve on another supplier. After failover, keep Request-ID, effective supplier, model snapshot, and settlement data for reproduction and accountability.

Use cases

  • Choose channels while preserving model attribution
  • Govern multi-supplier routing and data boundaries

API protocols

  • /v1/models

FAQ

Are OpenRouter, AWS, or Azure model originators?

They primarily aggregate or host third-party models. Capability belongs to the originator; the platform guide describes hosting and protocol boundaries.

Should the same model be retested after changing channel?

Yes. Snapshot, region, parameter mapping, stream events, limits, data policy, and price can differ.

Why are there more channel choices than provider guides?

Channels also include aggregators, workflows, local runtimes, compatibility proxies, and account bridges that do not own a model family.

Official sources

  1. Amazon Bedrock Supported Models Official
  2. Azure AI Foundry Models Official
  3. OpenAI API Reference Official