Model Providers

Model providers give your workspace access to AI models. Every application you build needs models to function, and configuring providers at the workspace level means all team members can use them across all projects.

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System vs Custom Providers

System Providers are managed by Dify. You get immediate access to models without setup, billing through your Dify subscription, and automatic updates when new models become available. Best for getting started quickly. Custom Providers use your own API keys for direct access to model providers like OpenAI, Anthropic, or Google. You get full control, direct billing, and often higher rate limits. Best for production applications. You can use both simultaneously—system providers for prototyping, custom providers for production.

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Configure Custom Providers

Only workspace admins and owners can configure model providers. The process is consistent across providers:

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Supported Providers

Large Language Models:

• OpenAI (GPT-4, GPT-3.5-turbo)
• Anthropic (Claude)
• Google (Gemini)
• Cohere
• Local models via Ollama

Embedding Models:

• OpenAI Embeddings
• Cohere Embeddings
• Azure OpenAI
• Local embedding models

Specialized Models:

• Image generation (DALL-E, Stable Diffusion)
• Speech (Whisper, ElevenLabs)
• Moderation APIs

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Provider Configuration Examples

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Manage Model Credentials

Add multiple credentials for a model provider’s predefined and custom models, and easily switch between, delete, or modify these credentials. Here are some scenarios where adding multiple credentials is particularly helpful:

• Environment Isolation: Configure separate model credentials for different environments, such as development, testing, and production. For example, use a rate-limited credential in the development environment for debugging, and a paid credential with stable performance and a sufficient quota in the production environment to ensure service quality.
• Cost Optimization: Add and switch between multiple credentials from different accounts or model providers to maximize the use of free or low-cost quotas, thereby reducing application development and operational costs.
• Model Testing: During model fine-tuning or iteration, you may create multiple model versions. By adding credentials for these different versions, you can quickly switch between them to test and evaluate their performance.

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Configure Model Load Balancing

Model providers typically enforce rate limits on API access within a specific timeframe to ensure stability and fair use. For enterprise applications, a high volume of concurrent requests from a single credential can easily trigger these limits, disrupting user access. An effective solution is load balancing, which distributes request traffic across multiple model credentials. This prevents rate limit issues and single points of failure, ensuring business continuity and faster response times for all users. Dify employs a round-robin strategy for load balancing, sequentially routing model requests to each credential in the load balancing pool. If a credential hits a rate limit, it is temporarily removed from rotation for one minute to avoid futile retries. To configure load balancing for a model, follow these steps:

1. In the model list, find the target model, click the corresponding Config, and select Load balancing.
2. In the load balancing pool, click Add credential to select from existing credentials or add a new one.

3. Enable at least two credentials in the load balancing pool, then click Save. Models with load balancing enabled will be marked with a special icon.

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Access and Billing

System providers are billed through your Dify subscription with usage limits based on your plan. Custom providers bill you directly through the provider (OpenAI, Anthropic, etc.) and often provide higher rate limits. Team access follows workspace permissions:

• Owners/Admins can configure, modify, and remove providers
• Editors/Members can view available providers and use them in applications

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Troubleshooting

Authentication Failed: Verify API key accuracy, check expiration, ensure sufficient credits, confirm key permissions. Model Not Available: Check provider configuration includes the model, verify API key tier access, refresh provider settings. Rate Limits: Upgrade provider account, implement request queuing, consider custom providers for higher limits.