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Use this page to configure the language models available for chat, agents, and other text-based workflows in Onyx.
Image generation and voice are configured separately in Image Generation and Voice Mode.

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Language Models

Navigate to Admin Panel → Language Models to choose which providers your workspace can use, which models are visible, and which models should be the default or fast option in Onyx. Language Models page overview

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Provider Types

These providers give you direct access to a model vendor’s hosted API.Common choices include OpenAI and Anthropic. This is usually the simplest setup when you want fast access to the provider’s latest flagship models.
These providers expose language models through a broader cloud or routing layer.Common choices include Azure OpenAI, Amazon Bedrock, Google Vertex AI, OpenRouter, LiteLLM Proxy, and Bifrost. They are useful when you need enterprise controls, cloud alignment, regional hosting options, or access to multiple model families from one integration point.
These options let you run open-weight models on your own infrastructure or local hardware.Onyx includes built-in integrations for Ollama and LM Studio. This is a good fit when your team needs local development workflows, tighter data residency, or lower per-token costs.
If your provider is not listed directly, you can still connect it through an OpenAI-compatible API.This covers custom gateways, hosted inference endpoints, and internal model platforms that expose an OpenAI-style /chat/completions or /models interface.

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Choosing a Good Starting Setup

If cloud-hosted models are approved for your organization, they are usually the best default choice because they are easier to operate and generally provide the best capability-to-cost tradeoff.
  • Start with one primary provider for most users and one lower-cost fast model for background tasks.
  • Use a recent GPT, Claude, or Gemini family model as your default if you want the strongest out-of-the-box experience.
  • Use Bedrock, Vertex AI, Azure OpenAI, OpenRouter, LiteLLM Proxy, or Bifrost when procurement, routing, or cloud alignment matters more than a direct vendor integration.
  • Use open-weight families such as Llama, Qwen, DeepSeek, or gpt-oss if you are self-hosting.
  • Keep the visible model list short so users are choosing between a few intentional options instead of every possible version.
Self-hosting is best for advanced teams that already know which models they want to run and how they will operate them.

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Configure Your Providers

OpenAI

Azure OpenAI

Anthropic

AWS Bedrock

Google Vertex AI

OpenRouter

Bifrost

LiteLLM Proxy

Ollama

LM Studio

OpenAI-Compatible Providers

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Best Practices

  • Review the terms, privacy posture, and data processing terms of every provider you enable.
  • Limit the visible model list to the models you actually want users to choose from.
  • Use private providers and access controls for costly, experimental, or team-specific models.
  • Decide on a default model and a fast model before rolling the page out broadly.
  • Make sure internal guidance is clear about what data users can send to each provider.