Overview
The Swarms API provides a diverse range of multi-agent architectures, each designed to solve specific types of problems and workflows. These architectures enable you to orchestrate multiple AI agents in various patterns, from simple sequential workflows to complex hierarchical systems. Understanding the available architectures helps you select the optimal pattern for your use case, whether you need parallel processing, consensus-based decision making, or dynamic task routing. Multi-agent architectures can be combined and nested to create sophisticated systems that leverage the strengths of different patterns. Each architecture type has unique characteristics that make it suitable for specific scenarios, such as linear processing pipelines, collaborative problem-solving, or high-throughput batch operations. The flexibility of these architectures allows you to build custom solutions that match your exact requirements.Available Architectures
The following table provides a comprehensive list of all available multi-agent architectures in the Swarms API:Architecture Categories
The available architectures can be broadly categorized into several groups: Workflow Patterns:SequentialWorkflow, ConcurrentWorkflow, GraphWorkflow, and BatchedGridWorkflow provide different execution patterns for organizing agent tasks.
Collaboration Patterns: GroupChat, MixtureOfAgents, and MajorityVoting enable agents to work together collaboratively.
Routing & Organization: MultiAgentRouter, HierarchicalSwarm, AgentRearrange, RoundRobin, and PlannerWorkerSwarm help organize and distribute work among agents.
Specialized Systems: HeavySwarm and AutoSwarmBuilder provide specialized capabilities for specific use cases.
Decision & Evaluation: MajorityVoting, CouncilAsAJudge, DebateWithJudge, and LLMCouncil focus on decision-making and evaluation processes.
Getting Started
To use any of these architectures, make a request to the/v1/swarm/completions endpoint with the swarm_type parameter set to your desired architecture. For detailed information about each architecture, including usage examples and best practices, follow the links in the table above or refer to the Multi-Agent Overview page.