Open-Source vs Hosted AI Agent Platforms: Differences 2026
The short answer
Open-source agent systems give you control; hosted agent systems give you speed. With an open-source framework or platform you run the agent loop, tools and state on your own infrastructure, with any model. With a hosted platform the vendor runs the harness and the sandbox, and you configure the agent through an API.
| Open-source / self-hosted | Hosted / managed | |
|---|---|---|
| Examples (Oct 2026) | LangGraph (MIT), n8n (fair-code, self-host or cloud) | Claude Managed Agents (beta), Amazon Bedrock AgentCore |
| Model choice | Any model, swap freely | Vendor’s models (Anthropic) or the cloud’s catalogue |
| Where data lives | Your environment; air-gap possible | Vendor’s runtime and logs |
| Sandbox & isolation | You build it | Included (e.g. AgentCore microVMs) |
| Scaling & upgrades | Your job | Vendor’s job |
| Cost model | Compute + tokens + your engineering time | Tokens + per-use runtime charges |
| Lock-in | Low (framework code is portable) | Higher (runtime APIs, session formats) |
| Time to production | Weeks | Days |
What you get with open source
LangGraph is a low-level orchestration framework for long-running, stateful agents: durable execution that resumes after failures, human-in-the-loop interrupts to inspect and edit state, and memory. It is MIT-licensed and used by Klarna, Replit and Elastic per its repository. Its higher-level Deep Agents package adds planning, subagents and file-system tools.
n8n is a visual workflow and agent platform with 1,500+ integrations, 9,000+ templates, JavaScript and Python code steps, human approvals, role-based access and audit trails. Self-host it or use n8n Cloud. Note the licence: fair-code, not OSI open source.
What open source costs you: secrets handling, network egress rules, a sandbox for code execution, logging, retries, and upgrading the stack every time a model API changes.
What you get with hosted
Claude Managed Agents is Anthropic’s pre-built agent harness running in managed infrastructure, in beta behind the managed-agents-2026-04-01 header. Claude can read files, run commands, browse the web and run code in a secure environment, with prompt caching and context compaction built in. It is also available on Claude Platform on AWS.
Amazon Bedrock AgentCore is modular: Runtime, Gateway, Identity, Policy, Memory and more, each usable alone. Runtime microVMs bill per second on actual CPU and memory with a 1-second minimum; CPU scales to zero during I/O wait such as waiting for the model, and Runtime v2 reclaims idle memory after 120 seconds. New AWS customers get up to $200 in Free Tier credits.
What hosted costs you: portability. Session formats, tool definitions and memory stores are vendor-specific, and your prompts and tool outputs pass through the vendor’s runtime.
How to choose
- Regulated data, air-gapped, or sovereignty requirement: open source, self-hosted.
- One model vendor, need production in days: hosted harness from that vendor.
- Business workflows with many SaaS integrations, mixed technical team: n8n (self-host for data control).
- Custom, long-running agents with complex state, multi-model: LangGraph on your infrastructure or a managed deployment.
- Unsure: keep agent logic in an open framework and run it on a hosted runtime such as AgentCore, which accepts multiple frameworks. You keep the code portable and outsource the sandbox.
Whichever you pick, the security baseline is the same: deny-by-default networking, short-lived scoped credentials, an audit log of every tool call and human approval for irreversible actions — see how to give AI agents credentials without leaking them. The harness-level version of this choice is in hosted agent harness vs DIY agent loop.
Last verified: October 9, 2026.