Agno vs Mastra — two production runtimes, two stacks
Agno Python, FastAPI, near-zero overhead
target: ~2μs agent instantiation
matters for thousands of short-lived agents per second
target: ~3.75 KiB memory per agent
stateless FastAPI handler per request
~23 model providers, native multimodal
text, image, audio, video, file
"no graphs, chains, or convoluted patterns"
philosophy: pure python, minimal framework surface
session state in DB; agent is ephemeral
Mastra TypeScript, Vercel AI SDK substrate
three primitives: Agents, Tools (Zod), Workflows
Zod-typed tools; compile-time safety
Unified Model Router: 3,300+ models, 94 providers
single client across the ecosystem (Mar 2026)
composite storage: memory / workflows / obs
ClickHouse recommended at observability scale
server adapters: Express, Hono, Fastify, Koa
first-class Next.js + Astro integration
Mastra Studio at localhost:4111 for debugging
choose by stack
python backend + FastAPI + short-lived agents Agno
typescript backend + Next.js/Vercel + unified multi-provider Mastra
durable state, explicit graphs, long-horizon runs LangGraph (Lesson 13)
performance targets matter when overhead is a bottleneck; often it is not.