Google Agent Development Kit (ADK) vs Manifest

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

	Google Agent Development Kit (ADK) Agents	Manifest Agents
Tagline	Google's open-source framework for building, evaluating, and deploying production AI agents	Open-source LLM router that fans your agent traffic across providers and your existing AI subscriptions.
Category	Agents	Agents
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).	Freemium· Free: $0 /month · Pro: $19 /month · Enterprise: Let's Talk · Open Source: Free · Enterprise: Custom pricing
Model	Gemini (default) plus Claude, GPT-4/5, Llama, and other providers via LiteLLM	Multi-model
Editorial score	—	7.1 / 10
Use cases	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	llm-routingcost-controlagent-infrastructurefallback-handlingmulti-provider
Pros	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	OpenAI-compatible endpoint, so most SDKs and agent harnesses drop in unchanged Per-tier fallbacks keep agents running through provider outages and rate limits Auto-fix silently corrects deprecated model IDs and bad parameters Self-hostable via Docker with support for local runtimes (Ollama, LM Studio, Llama.cpp) BYOK plus subscription routing lets you actually use the ChatGPT/Claude plans you already pay for
Cons	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	Adds a network hop and another moving piece to debug when calls fail Managed cloud is still early access; production users are mostly on self-host Routing rules and budgets only help if you actually configure them thoughtfully
Website	google.github.io	manifest.build

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

Pick Manifest if

✅ OpenAI-compatible endpoint, so most SDKs and agent harnesses drop in unchanged
✅ Per-tier fallbacks keep agents running through provider outages and rate limits
✅ Auto-fix silently corrects deprecated model IDs and bad parameters
✅ Self-hostable via Docker with support for local runtimes (Ollama, LM Studio, Llama.cpp)

Compare a different pair →