Augment Code vs Google Agent Development Kit (ADK)

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

	Augment Code Agents	Google Agent Development Kit (ADK) Agents
Tagline	Enterprise agent-orchestration platform for the software development lifecycle.	Google's open-source framework for building, evaluating, and deploying production AI agents
Category	Agents	Agents
Pricing	Paid· BUSINESS: $100/month · ENTERPRISE: Custom	Free· Framework itself is free and open-source (Apache 2.0). Costs come from the underlying model provider (e.g. Gemini API / Vertex AI usage) and any hosting infrastructure (Cloud Run, GKE, Agent Engine).
Model	Claude Opus, Claude Sonnet, Gemini, and open-source models via BYOK; routed by proprietary Prism model router	Gemini (default) plus Claude, GPT-4/5, Llama, and other providers via LiteLLM
Editorial score	—	—
Use cases	Automated pull-request reviewTest-coverage expansion on legacy codeIncident triage from Slack alertsSecurity vulnerability remediationPR authoring and description generationWork-item triage in JiraMulti-repo refactor orchestrationCI/CD-embedded agent workflowsCustom expert agent authoring	Multi-agent research assistantCustomer support triage agentRAG chatbot backed by Vertex AI SearchCode review and refactoring agentBigQuery natural-language analytics agentDocument processing pipelineVoice/streaming conversational agentInternal tool-use agent orchestrating APIsEvaluation and regression testing of LLM workflowsEnterprise workflow automation on Agent Engine
Pros	Orchestrates multiple specialised agents rather than a single chat assistant, which scales better across large orgs Prism router picks a model per turn and reports 20-30% cost reduction versus single-model setups Proprietary Context Engine indexes large codebases structurally, cutting token spend without quality loss Deep enterprise posture: SOC 2 Type II on Business, plus CMEK, ISO 42001, SSO/SCIM and SIEM on Enterprise Deployment flexibility across laptop, cloud VM, Augment cloud, or self-hosted AWS/GCP BYOK support for Claude, Gemini and open-source models avoids vendor lock-in on inference Pre-built experts for code review, PR authoring, incident response and security remediation ship day one	Genuinely open-source (Apache 2.0) with active Google engineering behind it, not a hosted-only product Multi-language: first-class Python, Java, and Go SDKs — rare among agent frameworks that are usually Python-only Built-in dev UI (`adk web`) with trace inspection, event stream, and session replay speeds up debugging enormously Model-agnostic via LiteLLM — Gemini is default but Claude, GPT, and local models plug in cleanly Rich multi-agent primitives out of the box: SequentialAgent, ParallelAgent, LoopAgent, and hierarchical sub-agents Tight Google Cloud integration for deployment (Cloud Run, GKE, Agent Engine) plus native BigQuery/Vertex Search tools Evaluation harness with trajectory-level scoring is included, not a separate paid add-on First-class MCP (Model Context Protocol) client and server support
Cons	No public free tier; the $100/mo Business floor prices out solo devs and hobbyists Pitched at platform/DevEx teams, so individual engineers get less value than from Cursor or Copilot Cosmos is a young platform and the expert registry is still shallow versus mature CI/CD ecosystems Usage top-ups expire 12 months after purchase, which penalises bursty adoption No open-source release and no publicly documented REST API for third-party integrators	Documentation and examples lean heavily on Gemini + Google Cloud; non-Google paths work but feel like second-class citizens API surface is still evolving — breaking changes between minor versions have been common through 2025-2026 Multi-agent orchestration primitives are powerful but the graph/callback model has a real learning curve compared to a plain prompt loop Agent Engine deployment is convenient but locks you into GCP billing and quotas TypeScript/Kotlin support lags the Python SDK in features and community examples
Website	www.augmentcode.com	google.github.io

Pick Augment Code if

✅ Orchestrates multiple specialised agents rather than a single chat assistant, which scales better across large orgs
✅ Prism router picks a model per turn and reports 20-30% cost reduction versus single-model setups
✅ Proprietary Context Engine indexes large codebases structurally, cutting token spend without quality loss
✅ Deep enterprise posture: SOC 2 Type II on Business, plus CMEK, ISO 42001, SSO/SCIM and SIEM on Enterprise

Pick Google Agent Development Kit (ADK) if

✅ Genuinely open-source (Apache 2.0) with active Google engineering behind it, not a hosted-only product
✅ Multi-language: first-class Python, Java, and Go SDKs — rare among agent frameworks that are usually Python-only
✅ Built-in dev UI (`adk web`) with trace inspection, event stream, and session replay speeds up debugging enormously
✅ Model-agnostic via LiteLLM — Gemini is default but Claude, GPT, and local models plug in cleanly

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