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Antigravity 2.0 vs Legioni

Antigravity 2.0 and Legioni are both cli coding agents tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

Antigravity 2.0

Antigravity 2.0

The vendor describes Project IDX as a browser-based IDE where agents handle multi-step coding tasks end-to-end: writing code, executing it, observing what breaks in a live preview, and self-correcting before handing back control. Multi-model support means you are not locked to a single provider when one model handles your stack better than another. The free tier exists but carries usage caps that surface quickly on longer agentic runs — teams hitting those caps mid-task face a hard stop, not a graceful queue. Browser-based architecture removes local setup friction but also removes offline access and the deep editor customization that engineers who have spent years tuning their environment tend to miss.

Legioni

Legioni

The orchestrator receives a plain-language task in opencode, breaks it down, and hands it to a chain of specialist agents — architect, implementer, reviewer, test-strategist — in sequence. Each step feeds the next; the loop closes only when tests pass. The 'lesson promotion' mechanism lets teams encode what they learn into persistent agent behavior, so the same mistake doesn't resurface two projects later. The hard boundary: Legioni runs inside opencode, full stop. If your team is not already on opencode or cannot adopt it, the architecture is irrelevant — there is no standalone path and no API to route through a different runtime.

AttributeAntigravity 2.0Legioni
PricingPaidFree
Price$0-$200/month
Free trialNoNo
Open sourceNoYes
Has APIYesNo
Self-hosted optionNoYes
PlatformsmacOS, Windows, Linux, Web-basednpm, Node.js
Released2025-11
Pros
  • Self-verifying execution loop — the agent runs code, observes live browser output, and revises without waiting for you to relay what broke, which means you stop being the error-relay between your AI tool and your test environment.
  • Multi-model support in a single environment, so switching the underlying model when one handles your framework better is a configuration change rather than a tool migration.
  • Browser-based access with no local setup, which means onboarding a new developer or spinning up a fresh environment takes minutes rather than an afternoon of dependency resolution.
  • Multi-agent task splitting lets separate agents handle discrete parts of a complex task in parallel, cutting the wall-clock time on multi-step workflows that a single-agent loop would process serially.
  • API access means the agentic core can be called from external pipelines, so teams integrating AI into CI or build systems are not forced to use only the browser interface.
  • Test-driven agent loop closes only when tests pass, so you are not manually checking whether the implementer's output actually works before shipping it to review.
  • Specialist agents handle discrete roles — architecture, implementation, review, test strategy — which means a single task does not collapse into one undifferentiated prompt that loses track of constraints halfway through.
  • Lesson promotion persists learned behaviors across sessions and projects, so teams stop re-encoding the same project rules every time they open a new task.
  • Zero-install path via npx means you can run `legioni init` in a new repo without touching your global Node environment, keeping adoption friction low for the first experiment.
  • MIT license and self-hosted operation mean the agents run entirely within your environment — no usage data leaves to a vendor API beyond whatever opencode itself sends.
Cons
  • Free tier usage caps terminate agentic runs mid-task when a multi-step job exceeds the allotment — there is no graceful queue, the session stops, and teams restart manually or upgrade to a paid tier before they have fully evaluated whether the tool fits.
  • No self-hosted option and no offline access: teams with data residency requirements, air-gapped environments, or security policies restricting cloud-only tooling cannot use this at all, and those teams move to locally-deployable alternatives rather than filing exception requests.
  • Browser-based execution means editor customization stops at what Google exposes in the interface — developers who depend on a specific plugin, language server configuration, or terminal workflow find the ceiling fast, and the path forward is maintaining a second local environment for the tasks IDX cannot handle.
  • Complex conditional branching across more than a few agents strains the multi-agent coordination layer; community reports describe tasks with deep dependency chains producing inconsistent results, and teams handling those workflows add manual checkpoints that undercut the automation they bought the tool to achieve.
  • Legioni is a hard dependency on opencode: every agent, every loop, every lesson runs inside opencode's runtime. Teams on Cursor, Cline, or any other AI coding environment cannot use this tool — the only path forward is adopting opencode first, which is a separate adoption decision with its own trade-offs.
  • The project's public repository shows five commits and a small star count, which means edge cases in the agent loop, lesson promotion conflicts, and stack detection failures are under-documented and under-reported. Teams hitting unexpected behavior have no community issue history to search and no support channel beyond filing a GitHub issue themselves.
  • Lesson promotion is a manual, explicit action — the agents do not automatically surface or apply learned behaviors without team intervention. Projects where nobody curates the promoted lessons see no compounding benefit across sessions, which makes the core differentiating feature opt-in rather than default.
Bottom line

Antigravity 2.0 is paid while Legioni is free; Legioni is open source; only Antigravity 2.0 exposes a public API. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Antigravity 2.0 and Legioni?

Antigravity 2.0 is Paid, while Legioni is Free and open source. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Antigravity 2.0 better than Legioni?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.

Antigravity 2.0 vs Legioni: which should I pick?

Pick Antigravity 2.0 if its pricing model, openness, or platform fit matches your constraints; pick Legioni otherwise. Check free-trial availability on each listing if you want to test before committing.

Comparison data is sourced and verified by the AIDiveForge data pipeline. AIDiveForge is editorially independent.