Compare Agno and Hermes Agent side by side. Both are tools in the Agent Frameworks category.
Updated April 29, 2026
Choose Agno if production-first design with stateless scaling and AgentOS runtime.
Choose Hermes Agent if best-in-class persistent memory across sessions.
Want to compare Agno and Hermes Agent on your own traffic?
Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 250+ models through one gateway. Free tier covers 10K traces per month. Setup in 5 minutes, no credit card.
| Category | Agent Frameworks | Agent Frameworks |
| Pricing | Free open-source | Free open-source |
| Best For | Python teams building production AI agents that want first-class deployment, observability, and multi-agent support | Solo developers and small teams who use AI agents daily and want one that learns and compounds over time |
| Website | agno.com | nousresearch.com |
| Key Features |
|
|
| Use Cases |
|
|
Curated quotes from Hacker News, Reddit, Product Hunt, and review blogs. Dates shown so you can judge whether early criticism still applies.
“Agno has emerged as one of the fastest-growing AI agent frameworks in 2026 — 39,100+ stars and a 424-contributor community.”
“Purpose-built for production with stateless scaling, session management, and enterprise features — closer to a 'framework + runtime + control plane' than just an SDK.”
“Memory is stored in your database — you own the data, not the vendor. That alone made it the right call for our compliance posture.”
“Smaller community than LangChain at production scale — but the documentation gap is closing fast.”
“Released February 2026; seven weeks later it hit 95,600 GitHub stars — the fastest-growing agent framework of 2026.”
“Hermes wins on learning depth and security posture. For a solo developer or small team that uses the agent daily for 6+ months, Hermes compounds over time in ways other agents cannot.”
“Agents with 20+ self-created skills complete similar future tasks 40% faster — but this improvement is domain-specific. Skills don't transfer across domains.”
“Memory complexity adds setup friction for casual users — the best benefits emerge after 6+ months of consistent use.”
Key criteria to evaluate when comparing Agent Frameworks solutions:
Agno (formerly Phidata) is an open-source Python framework for building production-grade AI agents and multi-agent systems. With 39,100+ GitHub stars and an active 424-contributor community, it's emerged as one of the fastest-growing agent frameworks in 2026.
Agno provides three integrated layers: a Python SDK for building individual agents and multi-agent teams, a stateless FastAPI runtime called AgentOS for production deployment, and a control plane UI for monitoring, session management, and team operations. It supports 23+ LLM providers (OpenAI, Anthropic Claude, Google Gemini, and more) and ships 100+ pre-built tool integrations including web search, data analysis, file operations, and Model Context Protocol (MCP) servers.
Memory and knowledge systems are first-class: user memories, session memories, and RAG knowledge bases are stored in your database — you own the data, not Agno. Recent v2.5.13 (March 2026) added ReliabilityEval for agent evaluation, enhanced AgentOS APIs for session management, and Slack interface improvements. Agno is positioned as the production-first alternative to LangChain/LangGraph for Python teams.
Hermes Agent is Nous Research's open-source autonomous AI agent with persistent memory — released February 2026 and the fastest-growing agent framework of 2026, hitting 95.6K GitHub stars in seven weeks. Unlike most agents that forget everything between sessions, Hermes maintains a curated memory of preferences, projects, environment, and lessons learned.
The memory system is layered: MEMORY.md and USER.md files live in ~/.hermes/memories/ and inject into the system prompt as a frozen snapshot at session start. On top of this, Hermes ships 8 external memory provider plugins — Honcho, OpenViking, Mem0, Hindsight, Holographic, RetainDB, ByteRover, and Supermemory — adding knowledge graphs, semantic search, automatic fact extraction, and cross-session user modeling.
Hermes also auto-generates skills: as the agent solves novel tasks, it captures the procedure as a reusable skill. Nous Research benchmarks show agents with 20+ self-created skills complete similar future tasks 40% faster (in tokens and time, not necessarily quality). The improvement is domain-specific — skills don't transfer across domains. Hermes is fully open-source and self-hostable, positioned as the agent that compounds in value the longer you use it.
Developer frameworks and SDKs for building autonomous AI agents with tool use, planning, multi-step reasoning, and orchestration capabilities.
Browse all Agent Frameworkstools →One platform for routing, observability, tracing, and evals across every LLM provider.