focused_action and extract_prompt operations.
Workflow-Level Model Configuration
When you create or edit a workflow in the dashboard, you can select which model the main agent should use.Selecting a Model
- Open the Workflows page in your dashboard
- Click to create a new workflow or edit an existing one
- In the workflow editor, find the Model selector
- Choose from the available model configurations
- Save your workflow
System Default Models
Cyberdesk provides pre-configured system defaults optimized for different tasks:| Model | Provider | Best For |
|---|---|---|
| Sonnet 4.5 (Thinking) | Anthropic | Main agent (default) |
| Sonnet 4.5 | Anthropic | Data extraction |
| GPT-5 Mini | OpenAI | Cache detection |
| Bedrock Sonnet 4.5 (Thinking) | AWS Bedrock | Fallback when primary fails |
Per-Action Model Overrides
The most powerful feature of model configuration is the ability to specify a different model for individual actions directly in your workflow prompts. This works for:focused_action— dynamic decisions and observationsextract_prompt— vision-based data extraction from screenshots
How to Specify a Model in Your Prompt
Use themodel="Model Name" parameter in your prompt text:
Using the Model Picker in the Prompt Editor
The prompt editor provides easy access to the model picker:- Slash menu: Type
/and select “Model Override” to insertmodel="" - Tab autocomplete: Start typing
modeland press Tab to autocomplete - Direct typing: Type
model=""and place your cursor inside the quotes
model="" quotes, a dropdown appears showing all available models. Use arrow keys to navigate, and press Enter or Tab to select.
Computer Use Models vs. Extraction Models
When you select a non-computer-use model, you’ll see a toast warning:“This model isn’t a known computer use model. Only use this for screenshots with extract_prompt.”
Example: Hybrid Model Strategy
Use different models for different parts of your workflow:- Use a thinking model for complex decisions in
focused_action - Use a faster model for bulk extraction with
extract_prompt - Optimize for both accuracy and cost
Automatic Fallbacks
Cyberdesk automatically handles model failures with a fallback chain:- Primary model fails (rate limit, timeout, etc.)
- Fallback 1 is attempted (typically Bedrock Sonnet 4.5)
- Fallback 2 is attempted if Fallback 1 also fails (typically Bedrock Sonnet 4)
Custom Model Configurations
Want to use a specific model, provider, or configuration? The Cyberdesk team can set up custom model configurations for your organization.Coming Soon: A self-service UI for creating custom model configurations is in development. In the meantime, contact the Cyberdesk team to request custom configurations.
What You Can Customize
- Provider: Choose from any supported provider
- Model: Select specific model versions
- Temperature: Control response randomness
- Max tokens: Set output length limits
- Timeout: Configure request timeouts
- API keys: Use your own provider API keys for billing and rate limits
Requesting a Custom Configuration
Contact the Cyberdesk team:- Email: [email protected]
- Discord: Join our community
- Which provider and model you want to use
- Any specific parameters (temperature, max tokens, etc.)
- Whether you’ll provide your own API key
Supported Providers
Cyberdesk uses LangChain’sinit_chat_model under the hood, which means we can support virtually any model from any provider. This includes:
Anthropic
Claude models including Sonnet, Opus, and Haiku variants
OpenAI
GPT-4, GPT-5, and other OpenAI models
AWS Bedrock
Access models through AWS infrastructure
Gemini models via Vertex AI or Google AI
Azure
Azure OpenAI and Azure AI services
And More
Groq, Mistral, Cohere, Together, and others
Best Practices
Start with Defaults
System defaults are optimized for most use cases. Only customize if you have specific requirements.
Match Model to Task
Use computer-use models for
focused_action, and consider faster/cheaper models for bulk extract_prompt operations.Test Model Changes
When switching models, test your workflows thoroughly. Different models may behave differently on the same tasks.
Monitor Performance
Track run success rates after model changes. Some models may perform better on specific workflow types.
Quick Reference
| Use Case | Recommended Approach |
|---|---|
| Main workflow agent | Set at workflow level in dashboard |
| Dynamic decisions during navigation | focused_action with computer-use model |
| Vision-based data extraction | extract_prompt (any vision model works) |
| Bulk extraction for output | extract_prompt with process_async and faster model |
| Cost optimization | Override with cheaper model for extraction tasks |
FAQ
Can I use my own API keys?
Can I use my own API keys?
Yes. Custom model configurations can use your own provider API keys. This gives you control over billing and rate limits. Contact the Cyberdesk team to set this up. Note that this will most likely result in a change to your Cyberdesk plan.
What happens if a model is deprecated?
What happens if a model is deprecated?
Cyberdesk monitors provider announcements and updates system defaults accordingly. For custom configurations, we’ll notify you in advance and help migrate to newer model versions.
Can I use different models for different actions?
Can I use different models for different actions?
Yes! Use the
model="Model Name" parameter in your prompts to override the model for specific focused_action or extract_prompt operations. This is the recommended way to optimize for accuracy and cost.Why can't I use all models for focused_action?
Why can't I use all models for focused_action?
focused_action requires models that understand computer use—clicking, typing, and navigating. Not all models have this capability. The model picker shows which models support computer use. Non-computer-use models work fine for extract_prompt since it only needs vision capabilities.How do I know which model to choose?
How do I know which model to choose?
Start with the system defaults. If you need more reasoning power for complex decisions, try a “Thinking” variant. For bulk extraction where speed matters, consider faster models like Sonnet without thinking. The model details panel in the picker shows each model’s characteristics.