Dropstone vs Grass: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Dropstone and Grass — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Dropstone
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Self-hosted AI agent with long-term memory that spans CLI, chat, SDK and real-world actions, running on open-weight models you host.
Key features
- Persistent Cross-Surface Memory: Teach the agent something once in the CLI and it already knows it in chat, in the SDK and on a phone call — memory persists per user across sessions and surfaces instead of dying with one login.
- Self-Hosted Open-Weight Stack: Run the entire agent inside your own walls on your keys, machines and network, using open weights the company hosts or local models through Ollama, so source code never leaves your infrastructure.
- Proactive Background Operation: The agent is already running rather than waiting to be opened — it monitors what you asked it to watch and hands back only the decision that was actually yours.
- Approval-Gated Real-World Actions: Control smart-home devices, monitor an inbox around the clock, place phone calls and look up half-remembered contacts, with every action gated behind an explicit approval.
- 1M-Token Context on Every Tier: A one-million-token context window is included even on the free plan, letting the agent hold an entire repository in mind at once.
- Model-Agnostic Tiering: Dropstone Fast, Pro and Heavy each run whatever tops the open-weight leaderboards that month rather than being tied to a single lab.
- Learned Skills: The agent picks up skills it does not yet have, retains them and reuses them without being asked twice, with the skill list growing month over month.
- Multi-Surface Access: Reach the same agent through the Dropstone CLI, a web dashboard, VS Code / Cursor / Windsurf extensions and Remote MCP connectors, with sandboxed code execution and plan mode before changes apply.
Best for
- Air-Gapped Engineering Teams: Ship real code with an AI agent while keeping the models, the repository and the network entirely inside company infrastructure.
- Always-On Inbox Triage: Let the agent watch an inbox around the clock and surface or act on the messages that matter instead of checking it yourself.
- Terminal-Native Development: Use the CLI agent to generate code, run it in a sandbox and open diffs, with plan mode and approval gates before anything is applied.
- Personal Operations Automation: Hand off recurring real-world tasks — smart-home control, placing a call, chasing a contact — to an agent that already has your context.
- Cost-Sensitive Heavy Usage: Get several times more weekly coding usage per dollar than subscription coding CLIs by running on self-hosted open-weight models.
- Custom Agent Integration: Embed the same memory-backed agent into your own stack through the SDK and Remote MCP connectors.
Grass
Grass
VM-first compute platform that gives coding agents a dedicated, always-ready virtual machine for running and testing code without local setup.
Key features
- Dedicated VM Allocation: Provides each coding agent with a dedicated virtual machine that is pre-provisioned and kept ready to execute code, eliminating per-run provisioning delays and local resource use.
- Zero-Configuration Runtime: Removes developer setup and configuration by supplying preconfigured runtimes so agents can run, test, and iterate on code immediately.
- Agent Integrations: Works natively with agent runtimes such as Claude Code and OpenCode to allow LLM-based agents to connect directly to the VM environment for code execution and debugging.
- Free Trial Hours: Offers an initial free allocation (10 hours) so teams can evaluate the platform and run early experiments without payment.
- Remote Execution & Isolation: Executes agent workloads inside isolated VMs to protect developer machines from heavy compute, long-running processes, or accidental resource exhaustion.
- Warm VM Availability: Keeps VM instances ready-to-use to reduce cold-start latency for interactive agent-driven coding sessions.
- Provisioned, dedicated VM per coding agent that stays ready to run tasks
- No local setup or configuration required
- Compatibility stated with Claude Code and OpenCode agent platforms
- Managed compute to avoid using developer laptop resources
- Free initial allocation (10 hours) to start
Best for
- Agent-driven Code Testing: Run language-model-based coding agents to generate, compile, and run test suites in a safe remote VM without installing dependencies locally.
- Offloading Heavy Builds and Tests: Execute CPU- or memory-intensive compilation and test jobs in remote VMs to avoid overloading developer laptops or CI runners.
- Interactive Agent Pair-Programming: Connect Claude Code or OpenCode agents to a persistent VM for fast, iterative coding and debugging sessions with immediate execution feedback.
- Automated Repair and Refactoring: Allow agents to run refactoring scripts or automated repair tools on real runtime environments and verify results in-isolation.
- Prototyping and Experimentation: Quickly spin up agent-backed development environments to prototype integrations or reproduce bugs using a predictable, preconfigured VM.
- Running autonomous coding agents that need persistent compute
- Offloading heavy or long-running code execution from developer machines
- Integrating external code-focused LLM agents (e.g., Claude Code, OpenCode) with dedicated runtime environments
- Quick experimentation with agents using the free trial hours before committing to paid plans