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Runtimes are the execution engines that power your Kubiya agents. They determine how your agents process requests, interact with tools, manage conversations, and integrate with different LLM providers. Choosing the right runtime ensures optimal performance, cost efficiency, and capabilities for your specific use case.

Agno Runtime

Multi-model runtime with support for all major LLM providers

Claude Code Runtime

Code-specialized runtime optimized for development workflows

Custom Runtimes

Extend with your own framework (LangChain, CrewAI, AutoGen)

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What Are Runtimes?

A runtime is the execution layer that sits between your agent’s configuration and the underlying AI model. It handles:
  • Model Integration: Routing requests to different LLM providers (OpenAI, Anthropic, Google, etc.)
  • Tool Execution: Managing Skills and MCP servers for agent capabilities
  • Conversation Management: Maintaining context and history across multi-turn interactions
  • Streaming & Feedback: Providing real-time execution updates
  • Performance Optimization: Caching, batching, and efficient token usage
Kubiya’s runtime-agnostic architecture lets you choose the execution engine that best fits your needs - whether it’s a built-in runtime or your own custom implementation.

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Quick Comparison

FeatureAgnoClaude Code
FrameworkAgno + LiteLLMClaude Code SDK
Model SupportAll providersClaude only
Best ForMulti-model workflowsCode & development
Max History100 messages200 messages
SpecializationProvider flexibilityDevelopment-optimized

Full Feature Comparison

See detailed side-by-side comparison of all capabilities

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Get Started

1

Choose Your Runtime

Determine which runtime best fits your use case:
  • Multi-model flexibility needed? → Agno Runtime
  • Code generation & analysis? → Claude Code Runtime
  • Specialized framework (LangChain, CrewAI)? → Custom Runtime

Compare Runtimes

Use our decision matrix to choose the right runtime
2

Configure Your Agent

Select the runtime when creating an agent:Via CLI:
kubiya agent create my-agent \
  --runtime agno \
  --model kubiya/claude-sonnet-4
Via API:
curl -X POST https://control-plane.kubiya.ai/api/v1/agents \
  -H "Authorization: Bearer $KUBIYA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "my-agent",
    "runtime": "agno",
    "model_id": "kubiya/claude-sonnet-4"
  }'

Agent Configuration

Learn about agent creation and configuration
3

Execute and Monitor

Your agent will execute using the selected runtime. Monitor performance, token usage, and tool execution through the Kubiya dashboard.

Analytics & Monitoring

Track runtime performance and optimize costs

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Built-in Runtimes

Agno Runtime

Multi-model flexibility via LiteLLM
  • All LLM providers (GPT, Claude, Gemini, Mistral, Cohere)
  • Python-based tool integration
  • MCP server support
  • 100-message conversation history
  • Flexible execution engine
Best for: Multi-model workflows, provider flexibility, general automation

Claude Code Runtime

Code-optimized execution
  • Claude models only (optimized integration)
  • Advanced file operations
  • Repository analysis capabilities
  • 200-message extended history
  • Session resumption for multi-turn
Best for: Code generation, refactoring, development workflows, technical documentation

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Extend with Custom Runtimes

Need specialized capabilities? Build your own runtime using popular frameworks:
Integrate LangChain’s ecosystem of tools, chains, and agents. Build custom runtimes that leverage LangChain’s composability while using Kubiya’s orchestration layer.
Create runtimes that coordinate multiple specialized agents using CrewAI’s role-based architecture. Perfect for complex workflows requiring agent collaboration.
Build runtimes using Microsoft’s AutoGen framework for advanced multi-agent conversations, code execution, and iterative problem-solving.
Implement the BaseRuntime interface to integrate any Python-based AI framework. Full control over execution logic, tool integration, and model interaction.

Custom Runtime Developer Guide

Complete guide with code examples, patterns, and best practices

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Explore Documentation

Understanding Runtimes

Learn how runtimes work and fit into the Kubiya architecture

Runtime Comparison

Side-by-side feature comparison and decision framework

Custom Runtimes

Build your own runtime with custom frameworks

Control Plane

Runtime registry and orchestration

Agents

Configure agents with runtime selection

Skills

Tools and capabilities available to runtimes

Control Plane

Runtime registry and orchestration