ZuploZuplo
LoginStart for Free
  • Documentation
  • API Reference
Getting Started
    Develop in the portal
      1 - Setup Your Gateway2 - Rate Limiting3 - API Key Auth4 - Deploy5 - Dynamic Rate LimitingDynamic MCP Server - Quickstart
    Develop locally with the CLI
      1 - Setup Your Gateway2 - Rate Limiting3 - API Key Auth4 - Deploy5 - Dynamic Rate LimitingDynamic MCP Server - Quickstart
Concepts
API Management
AI Gateway
    OverviewGetting StartedSource ControlUniversal API
    Providers
      OverviewManaging ProvidersAzure AIBedrock MantleVertex AICustom Providers
    Teams
    Apps
    Policies
    Cookbooks
    Integrations
MCP Gateway
MCP Server
Developer Portal
Development
Deploying & Source Control
Analytics
Observability
Networking & Infrastructure
Account Management
Programming API
Build with AI
Zuplo CLI
Migration Guides
Platform LimitsVersion Support PolicySecuritySupportTrust & ComplianceChangelog
powered by Zuplo
Providers

AI Providers

Zuplo's AI Gateway supports integration with various AI providers, allowing you to leverage different models and services for your apps.

Supported Providers

Zuplo currently supports the following AI providers:

  • OpenAI
  • Anthropic
  • Google
  • Mistral
  • xAI (Grok)
  • Azure AI—Azure OpenAI and Microsoft Foundry resources, serving Claude and every Foundry model family from your own Azure subscription
  • Bedrock Mantle—Amazon Bedrock's compatible-APIs endpoint, serving Claude models and models from many other vendors
  • Vertex AI—Google Cloud's managed model platform, serving Gemini and Model Garden models on your own Google Cloud project
  • Zuplo Demo—a free, keyless provider for trying the gateway
  • OpenAI-compatible Custom Providers (such as Qwen, Kimi, etc)

The following capabilities are supported across providers:

ProviderChat CompletionsEmbeddingsResponsesMessages
OpenAI✅✅✅❌
Anthropic✅❌❌✅
Google✅✅❌❌
Mistral✅✅❌❌
xAI✅✅❌❌
Azure AI✅✅✅✅
Bedrock Mantle✅❌✅✅
Vertex AI✅✅❌✅
Zuplo Demo✅❌❌❌
OpenAI-compatible (Custom)✅✅❌❌

Responses is the OpenAI Responses API (/v1/responses), and Messages is the native Anthropic Messages API (/v1/messages). See the Universal API for the endpoint each capability maps to.

Bedrock Mantle's capabilities depend on the model family: Claude models serve Messages (plus chat completions through translation), while its other models serve chat completions and—per model—Responses. See Using Bedrock Mantle.

Azure AI's capabilities split by model family, and within the OpenAI-compatible family they split per deployed model: a chat model serves chat completions and— per model and version—Responses, while an embedding model serves embeddings and neither of the others. Claude serves Messages (plus chat completions through translation) and needs a Microsoft Foundry resource, since Claude can't be deployed on an Azure OpenAI resource. Azure also addresses models by deployment name rather than by published model ID, so a deployment named differently from the model it serves needs mapping for the gateway to price it. See Using Azure AI.

A custom provider must serve chat completions and embeddings under a /v1 path segment on its API URL, and you enter that URL as an origin root—without the /v1 suffix vendors usually publish. See Custom Providers for the exact contract.

Apps reference a provider's models as providerName/model—for example openai/gpt-5-mini or anthropic/claude-sonnet-4-6—where providerName is the name you give the provider configuration. See the Universal API.

Azure AI

Azure AI serves models from your own Azure resource. One provider configuration covers both kinds of resource, and which capabilities apply depends on the resource and the model:

  • An Azure OpenAI resource deploys OpenAI models and serves chat completions, embeddings, and the Responses API.
  • A Microsoft Foundry resource serves those plus every Foundry model family—Grok, DeepSeek, Llama, Mistral, Phi, Kimi and more—and serves Claude models on the native Anthropic Messages API, with chat completions through the gateway's translation.

Two things make Azure different from every other provider:

  • It addresses deployments, not published model IDs. You name deployments when you create them in Azure, and that name is what goes in the model field. A deployment whose name differs from the model it serves needs a mapping, or the gateway can't price its usage.
  • Its endpoint host embeds your resource name. The provider dialog asks for an Azure Resource Name and a host family rather than a full URL, and it takes a resource key—not a Microsoft Entra ID token.

For prerequisites, setup steps, code examples, and troubleshooting, see Using Azure AI.

Bedrock Mantle

Bedrock Mantle is Amazon Bedrock's compatible-APIs endpoint. One regional endpoint and one long-term Bedrock API key serve two model families, and which capabilities apply depends on the model you call:

  • Claude models (for example anthropic.claude-sonnet-5) serve the native Anthropic Messages API, and chat completions through the gateway's translation.
  • OpenAI-compatible models—everything else Mantle serves, from open-weight models such as openai.gpt-oss-120b to frontier models such as openai.gpt-5.6-sol—serve chat completions and, per model, the OpenAI Responses API.

Mantle endpoints are regional, so the provider dialog asks for an AWS Region instead of an endpoint URL, and it accepts only long-term Bedrock API keys, which start with ABSK. For prerequisites, setup steps, code examples, and troubleshooting, see Using Bedrock Mantle.

Vertex AI

Vertex AI is Google Cloud's managed model platform. One provider configuration serves both the Gemini family and Vertex's Model Garden partner models—DeepSeek, Qwen, GLM, Kimi, MiniMax, Gemma, and GPT-OSS—from your own Google Cloud project, on your Google Cloud billing.

Two things make its setup different from every other provider:

  • It authenticates with a service account, not an API key. Vertex's prediction endpoints reject API keys, so the dialog asks for a service account JSON key file and the gateway exchanges it for short-lived access tokens.
  • It needs a Google Cloud project as well as a location. Vertex endpoints are per-location, and the project isn't part of the endpoint, so the dialog asks for both.

Every Vertex model ID is publisher-qualified, so a model reference has two slashes: a provider named vertexai serves vertexai/google/gemini-3.7-flash, vertexai/qwen/qwen3-coder-480b-a35b-instruct-maas, and vertexai/anthropic/claude-haiku-4-5@20251001. Model availability varies by location—most Model Garden models are served only from the global location, and Google's regional endpoints serve Claude Sonnet 4.6 and earlier only, so global is the location that serves every Claude model. Vertex's Claude models serve the native Anthropic Messages API (/v1/messages) and nothing else: they aren't available on /v1/chat/completions, and each one must be enabled in Model Garden for your Google Cloud project before it answers.

For prerequisites, Google Cloud setup, provider steps, code examples, and troubleshooting, see Using Vertex AI.

Zuplo Demo

Zuplo Demo is a free provider that Zuplo operates so you can try the AI Gateway without an account with an LLM provider. Add it like any other provider—see Managing Providers—but skip the API key: the dialog doesn't ask for one, because your gateway authenticates to the demo service itself.

The provider serves three demo persona models as chat completions, at no cost:

  • zuplodemo/pirate
  • zuplodemo/wizard
  • zuplodemo/space-cowboy

Not for production use

Zuplo Demo has daily limits for each Zuplo account—plenty for exploring the gateway and demos, but not for real traffic. Swap in a keyed provider such as OpenAI or Anthropic before going live.

If you need support for additional providers or capabilities, please contact us at support@zuplo.com. We're continually working to add support for more providers based on customer demand.

Edit this page
Last modified on September 10, 2026
Universal APIManaging Providers
On this page
  • Supported Providers
  • Azure AI
  • Bedrock Mantle
  • Vertex AI
  • Zuplo Demo