E2B vs Google Agent Development Kit (ADK)

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

	E2B Agents	Google Agent Development Kit (ADK) Agents
Tagline	Secure cloud sandboxes for running AI-generated code	Google's open-source framework for building, evaluating, and deploying production AI agents
Category	Agents	Agents
Pricing	Freemium· Hobby: Free · Pro: $150 · Ultimate: Contact us for custom solution with special pricing	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	LLM-agnostic (works with GPT-4o, Claude, Mistral, Llama, and self-hosted models)	Gemini (default) plus Claude, GPT-4/5, Llama, and other providers via LiteLLM
Editorial score	—	—
Use cases	Code interpreter for chat appsAutonomous coding agentsData analysis with pandas and matplotlibBrowser-use and computer-use agentsLLM tool execution backendSWE-agent style repo editsSecure sandbox for untrusted user codeMulti-agent workflow runtimeAI-generated report generationRAG pipelines with code execution steps	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	Sub-200ms sandbox startup with no cold starts, thanks to Firecracker microVMs True VM-level isolation, safe for arbitrary LLM-generated code and untrusted shell commands Long-running sessions up to 24 hours, enough for multi-step data or coding agents Open-source core with self-host and BYOC options for airgapped or regulated environments LLM-agnostic with first-party support in LangChain, LangGraph, LlamaIndex, and OpenAI/Anthropic SDKs Custom sandbox templates let teams pre-bake dependencies and skip package-install latency Generous $100 free-credit tier makes prototyping essentially free	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	Per-second usage billing on top of the $150/mo Pro fee can get expensive for high-volume agent traffic Concurrency cap of 100 sandboxes on Pro (extendable at extra cost) can bottleneck production apps Self-hosting requires operating Firecracker, which is nontrivial versus just calling an API Free Hobby tier is a one-time credit grant, not an ongoing free allowance Focused purely on execution infrastructure, no built-in agent framework, planner, or memory layer	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	e2b.dev	google.github.io

Pick E2B if

✅ Sub-200ms sandbox startup with no cold starts, thanks to Firecracker microVMs
✅ True VM-level isolation, safe for arbitrary LLM-generated code and untrusted shell commands
✅ Long-running sessions up to 24 hours, enough for multi-step data or coding agents
✅ Open-source core with self-host and BYOC options for airgapped or regulated environments

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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