Kastor vs Loma (2026)
A side-by-side comparison of Kastor and Loma on pricing, features, and fit, so you can decide which is right for you.
Quick answer
Kastor and Loma are both strong choices, but they fit different needs. Choose Kastor if you mainly need building multi-step research assistants that delegate subtasks to specialized sub-agents — its edge is completely free and open-source with no licensing fees or usage limits. Choose Loma if you need coordinating multiple llm-based agents that need shared knowledge to avoid conflicting outputs — its edge is completely free and open-source with no subscription or saas fees. Kastor starts at Free; Loma starts at Free.
Features compared
- Multi-agent orchestration framework for coordinating multiple AI agents simultaneously
- Open-source codebase with full transparency and community-driven development
- Extensible architecture supporting custom LLM backends and tool integrations
- Agent communication and context-sharing protocols for collaborative task execution
- Self-hosted shared memory layer deployable on your own infrastructure
- Company-wide knowledge store accessible by multiple AI agents simultaneously
- Recallable context that persists across agent sessions and team interactions
- Open-source codebase with full customization and integration flexibility
Pros & cons
- Completely free and open-source with no licensing fees or usage limits
- Gives developers full control over agent logic, memory, and integrations
- Active open-source community enables rapid iteration and community-contributed extensions
- Requires developer expertise to set up and configure compared to managed platforms
- Documentation and support may be limited compared to commercial multi-agent frameworks
- Completely free and open-source with no subscription or SaaS fees
- Full data privacy since everything runs on your own servers
- Enables true multi-agent coordination with a single shared memory source
- Requires technical expertise to self-host and maintain the infrastructure
- No managed cloud option for teams that prefer a hands-off deployment
The verdict
Choose Kastor if
you mainly need to building multi-step research assistants that delegate subtasks to specialized sub-agents. Its edge: completely free and open-source with no licensing fees or usage limits.
Choose Loma if
you mainly need to coordinating multiple llm-based agents that need shared knowledge to avoid conflicting outputs. Its edge: completely free and open-source with no subscription or saas fees.
Frequently asked questions
Is Kastor better than Loma?
Neither is universally better. Kastor is stronger for building multi-step research assistants that delegate subtasks to specialized sub-agents, with an edge in completely free and open-source with no licensing fees or usage limits. Loma is stronger for coordinating multiple llm-based agents that need shared knowledge to avoid conflicting outputs, with an edge in completely free and open-source with no subscription or saas fees. Pick based on your main task.
Which is cheaper, Kastor or Loma?
Kastor starts at Free and Loma starts at Free. Free tier: Kastor — Fully free and open-source; Loma — Fully free and open-source with no usage limits or paywalls.
What is Kastor best for?
Kastor is best for building multi-step research assistants that delegate subtasks to specialized sub-agents, automating complex workflows where multiple ai agents must collaborate and hand off results, prototyping agentic pipelines for startups or research teams without incurring api or platform costs.
What is Loma best for?
Loma is best for coordinating multiple llm-based agents that need shared knowledge to avoid conflicting outputs, storing and retrieving internal company knowledge for ai-assisted workflows, building internal ai assistants that remember prior context across departments.
Do Kastor and Loma have free plans?
Kastor: Fully free and open-source. Loma: Fully free and open-source with no usage limits or paywalls. Check each tool's pricing page for current limits, as plans change.