Agentic Index
Google Antigravity vs Kiro (2026)
This is Google against AWS in agentic IDEs. That verdict is the Agentic Index coverage score, graded from each vendor's own published materials.
Antigravity spans desktop, CLI, and SDK with a built in browser and strong multi model support. Kiro is spec driven, powered by Claude through Bedrock with automatic routing. Both are 20 dollars with free tiers, so the decision usually follows your cloud and your appetite for process.
On the Agentic Index coding agent ranking, neither Google Antigravity nor Kiro clears the bar, which asks for all five merge loop capabilities documented in full. Google Antigravity does not document knowledge grounding and RAG in full, nor testing, debugging and optimization; Kiro does not document testing, debugging and optimization in full, nor observability and auditability. 2 of the 65 vendors in the lane clear it. See the coding agent ranking
This comparison is published by Agentic Index, an independent agentic AI vendor research platform. Google Antigravity and Kiro are each graded against the same 14 capability Agentic Index taxonomy, from the vendor's own public materials under the Agentic Index verification standard, alongside 956 researched vendors. No vendor pays for placement and no vendor has reviewed this page. How this evidence is graded
Choose Google Antigravity if
- The built in browser matters for front end and full stack agents that must see what they build.
- You want multi model flexibility and MCP in a Google backed product.
- Your team prefers exploratory speed over mandatory specs.
Choose Kiro if
- Written specs before implementation match your review and compliance culture.
- AWS alignment: Bedrock, AWS procurement, and the Amazon Q Developer migration path.
- Multi surface coverage including iOS keeps work moving off the desktop.
| At a glance | Google Antigravity | Kiro |
|---|---|---|
| Category | Coding agent | Coding agent |
| Entry price | Free for individuals · Google AI Pro $19.99/mo · Ultra from $99.99/mo | Free (50 credits) · Pro $20/user/mo |
| Free / trial | Free tier | Free tier |
| Pricing confidence | public exact | public exact |
| Feature | G Google Antigravity |
K Kiro |
|---|---|---|
| Action & orchestration | ||
|
Integrations & Tool Calling Ability to connect agents to real systems through native integrations, OAuth-authenticated actions, custom tools, APIs, webhooks, or MCP-compatible tools. |
Full / Explicit | Full / Explicit |
|
Workflow Orchestration Ability to sequence, branch, retry, route, and combine deterministic workflow nodes with autonomous agent steps. |
Full / Explicit | Full / Explicit |
|
Triggers & Channel Coverage How agents wake up and where they work: schedules, webhooks, message events, CRM events, inbox events, chat, email, voice, and collaboration tools. |
Full / Explicit
A sidecar schedule runs agent commands on a cron expression with no user starting them, and agents are also invoked from the desktop app, the CLI, the SDK and IDE extensions. |
Full / Explicit
Upgraded from P: one unified agent harness across IDE, CLI, Web and Mobile with shared .kiro configuration, plus event driven hooks, headless mode, ACP, voice, and 24/7 Crew operation. |
| Knowledge & context | ||
|
Knowledge Grounding & RAG Ability to ground agent behavior in company data through document ingestion, retrieval, external knowledge APIs, semantic search, or RAG layers. |
Partial
The agent grounds on the project's code through codebase search, rules and installed skill bundles, plus outside data through MCP, but no persistent index over the customer's code is named. |
Full / Explicit
Upgraded from P: specs and steering are durable repository artifacts rather than conversational context, and the Web surface adds a named Memory feature; grounding is on the customer's own repository and standards. |
|
Memory & State Persistence Ability to persist context across a run, conversation, workflow, user, team, or longer-term memory layer. |
Partial
Projects and /resume carry session history, but no memory store with a stated scope, lifetime and delete path is documented. |
Full / Explicit
Upgraded from P: specs are durable repository state rather than session context, checkpoints allow rewind to any prior point, compaction manages long running context, and the Web surface ships a named Memory feature. |
| Control & trust | ||
|
Human Oversight & Guardrails Approval steps, consent checkpoints, escalation rules, structured guardrails, policy constraints, and pause/resume controls. |
Full / Explicit | Full / Explicit |
|
Security, Identity & Governance RBAC, SSO, auditability, encryption, least-privilege tool access, compliance posture, and data handling policy. |
Full / Explicit |
Full / Explicit
The docs are candid that MCP toggle and registry settings are client side enforced and can be circumvented by a user with administrative access to their own machine; recorded because it is a real limit on the governance claim, though the surface still clears the axis conjunction comfortably. |
|
Observability & Auditability Traces, logs, execution histories, metrics, audit events, and debugging detail for production agent behavior. |
Full / Explicit
The agent records its work as reviewable artifacts, including plans, walkthroughs, screenshots and browser recordings, and enterprise deployments log requests and responses for audit trails. |
Partial
Downgraded from F. Enterprise monitoring reports usage and activity at the organisation level, and checkpoints let a developer rewind, but neither is a per action execution trace reconstructing why the agent did something. Same reading applied to coderabbit and abnormal-ai in this session. |
|
Deployment & Data Residency Deployment modes and options, including SaaS, dedicated cloud, VPC, on-prem, hybrid, local runtime, and self-hosting. |
Full / Explicit
Enterprise deployment runs inside the organization's own Google Cloud project with global, US or EU multi region endpoints and VPC Service Controls. |
Full / Explicit |
| Solution readiness | ||
|
Prebuilt Agents, Templates & Packs Ready-made workflows, packaged employees, templates, blueprints, industry solutions, and role-specific agents that reduce time-to-value. |
Full / Explicit
Google publishes named bundles such as Modern Web Guidance, a Firebase bundle, Android CLI and DeepMind Science skills, installed and managed from the Customizations tab. |
Full / Explicit
Upgraded from P: Powers are a browsable, one click installable catalogue at kiro.dev/powers built on an open plugin standard, which is the axis rather than the customer authored steering and spec surfaces. |
| Platform extensibility | ||
|
Model Flexibility & Routing Ability to work across multiple foundation models, route tasks to different models, or let buyers bring their own providers and keys. |
Full / Explicit | Full / Explicit |
|
APIs, SDKs & MCP Extensibility Composability layer: stable APIs, SDKs, MCP tool consumption/serving, custom tools, and integration into internal systems. |
Full / Explicit | Full / Explicit |
|
Testing, Debugging & Optimization Testing, debugging, scoring, retries, fallbacks, quality gates, and optimization loops for improving agent workflows before and after deployment. |
Partial
The agent verifies its own work in a browser with screenshots, recordings and walkthroughs, but no harness for evaluating agent behavior is documented. |
Partial
Downgraded from F per the axis rule that this measures what the customer can test of the agent, not what the agent tests of the code. Property based verification against the spec is genuinely stronger than most coding agents offer, which is why this holds at P rather than N, but it validates output rather than evaluating agent behaviour. |
| Specialist automation | ||
|
Browser & Computer Use Browser, desktop, or remote/local computer control for workflows that cannot be handled through stable APIs alone. |
Full / Explicit |
Full / Explicit
Web sandbox sessions and MCP browser tooling exist, but neither is documented as the agent operating third party software that exposes no programmatic interface, which is the axis test. |
Pricing snapshot
Sourced from the Index pricing dataset · open each vendor's profile for full detail.
| Pricing | G Google Antigravity |
K Kiro |
|---|---|---|
|
Entry price Lowest public entry point |
Free for individuals · Google AI Pro $19.99/mo · Ultra from $99.99/mo | Free (50 credits) · Pro $20/user/mo |
|
Pricing confidence How public the numbers are |
Public, exact | Public, exact |
|
Billing Primary billing axis |
hybrid | credits |
|
Variable cost Workload / overage exposure |
Low variable cost | Low variable cost |
|
Free tier / trial Try before you buy |
Free tier
|
Free tierTrial
|
|
Buying motion Self-serve vs sales call |
Self-serve | Self-serve |
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