# Agno vs Caveman Agno records 140,302 monthly visits with -3.3% month-over-month growth and Contact for Pricing, Free pricing. Caveman records 171,826 monthly visits with -15.5% growth and Freemium, Contact for Pricing pricing. | Metric | [Agno](https://openaitools.app/tool/agno) | [Caveman](https://openaitools.app/tool/caveman) | | :--- | :--- | :--- | | Website URL | https://www.agno.com | https://caveman.so | | Categories | AI Agent, AI Developer Tools, Large Language Models (LLMs), Open Source AI Models | AI Developer Tools, AI Agent, AI Monitor, AI Productivity Tools | | Pricing Model | Contact for Pricing, Free | Freemium, Contact for Pricing | | Monthly Visits | 140,302 | 171,826 | | MoM Growth Rate | -3.3% | -15.5% | | Primary Market | India | United States | | Direct Visits | 78,790 | 64,225 | | Review Score | 4.6 | 4.7 | | Saved Count | 2 | 0 | | Supported Platforms | Website | Website | ## Agno Agno started life as a lightweight open-source library for building model-agnostic AI agents, and has grown into a full platform for shipping agents to production. The core is the Agno SDK, which offers three composable patterns — agents, teams and workflows — along with 100+ toolkits, memory, knowledge, structured I/O, guardrails, human-in-the-loop steps and evaluations. Because it is model-agnostic, it works with 30+ model providers and can also run agents built with other frameworks such as LangGraph, DSPy or the Claude SDK. Running agents reliably at scale is framed as a platform problem, so Agno pairs the SDK with AgentOS, a batteries-included runtime that turns agents into an API your product calls and an MCP server that assistants like ChatGPT and Claude can connect to. AgentOS adds durable execution, distributed state, session isolation, resumable streaming, JWT-based RBAC, audit logs, scheduling and deep observability, with a Control Plane UI for traces, sessions, evaluations and usage metrics. The distinguishing promise is control: agents deploy anywhere you can run a container — your cloud, on-premise or locally — and your data stays in your own database. The project has drawn a large open-source following (tens of thousands of GitHub stars) and is used by teams building support copilots, knowledge agents, research workflows and product-embedded assistants. **Pricing & Plans:** Agno offers a free open-source SDK, a free tier for getting started, and paid/enterprise plans (including an Enterprise option) for AgentOS, the Control Plane and commercial support. Exact plan pricing is quoted on request, so check the official pricing page for current numbers. - **Agno SDK with three patterns:** Compose agents, teams and workflows from simple primitives, with 100+ toolkits and reusable capabilities like memory, knowledge, structured output and guardrails. - **AgentOS runtime:** Turns agents into a production API and an MCP server with durable execution, distributed state, session isolation, resumable streaming, scheduling and JWT-based RBAC. - **Control Plane observability:** A mission-control UI for every agent, team and workflow run — traces, sessions, evaluations, token usage, audit logs, approvals and user roles. - **Model-agnostic by design:** Native support for 30+ model providers, plus the ability to run agents built with Agno, LangGraph, DSPy, the Claude SDK or your own code. - **Runs in your own cloud:** Deploy on any container platform — your cloud, on-premise or locally — and keep data in your own database while still powering a learning loop. **Strengths:** Open-source core with a large, active community and tens of thousands of GitHub stars; Model-agnostic: works across 30+ providers and can host agents built in other frameworks; Runs in your own cloud or on-premise, so data and infrastructure stay under your control; Batteries-included runtime and Control Plane cover the hard parts of stateful, distributed agents **Limitations:** The breadth of SDK, AgentOS and Control Plane can be a lot to learn for simple use cases; Commercial plan pricing is quote-based, so costs are harder to estimate up front; Getting full value out of observability and governance features assumes container/cloud deployment knowledge [Profile (Markdown)](https://openaitools.app/tool/agno.md) ## Caveman Caveman addresses a very concrete problem for teams running AI agents: token bills grow faster than the value the agents produce. The core agent and SDK are free and MIT-oriented, sitting entirely on your machine or inside your production app. When a turn happens, Caveman scans logs, test output, JSON, diffs and documents, shrinks them before the model ever sees them, and keeps the original on disk so the model can ask for it when it genuinely needs the exact text. Beyond reading, Caveman also trims what the agent writes and picks the model per turn. Its output compressor strips filler prose while returning code, commands and error text byte-for-byte, and its routing layer hands each sub-agent task to the cheapest model and effort level that still gets it right. The company publishes benchmark figures such as around 33% fewer input tokens across full sessions and roughly 0.46x cost per task compared with always-frontier-model routing. Caveman Cloud is the paid, hosted layer. It watches live traffic, surfaces where tokens are still wasted, tests each proposed fix against your own work, and only then ships it with proof. The Cloud Free plan covers a single developer, Team is $300 a month with $300 of usage included, and Enterprise runs inside your own VPC via a Helm chart with your KMS and storage. **Pricing & Plans:** Freemium, Contact for Pricing [Profile (Markdown)](https://openaitools.app/tool/caveman.md) ## Frequently Asked Questions ### How do Agno and Caveman compare in monthly traffic? Agno has 140,302 monthly visits, while Caveman has 171,826. Traffic estimates describe audience size, not product quality. ### How do their growth rates compare? Agno has a month-over-month growth rate of -3.3%; Caveman has -15.5%. ### How does pricing compare? Agno: Contact for Pricing, Free. Agno offers a free open-source SDK, a free tier for getting started, and paid/enterprise plans (including an Enterprise option) for AgentOS, the Control Plane and commercial support. Exact plan pricing is quoted on request, so check the official pricing page for current numbers. Caveman: Freemium, Contact for Pricing. Freemium, Contact for Pricing ## Alternatives | # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) | | :--- | :--- | :--- | :--- | :--- | :--- | :--- | | 1 | [Manus](https://openaitools.app/tool/manus) | 19,195,779 | -1.7% | Free Trial | A general-purpose AI agent that executes tasks, not just answers them | [.md](https://openaitools.app/tool/manus.md) | | 2 | [n8n](https://openaitools.app/tool/n8n) | 4,522,449 | -7.4% | Freemium | Node-based workflow automation platform combining robust visual automation with AI agent orchestration capabilities. | [.md](https://openaitools.app/tool/n8n.md) | | 3 | [MindStudio](https://openaitools.app/tool/mindstudio) | 1,793,337 | +14.2% | Contact for Pricing | No-code builder and deployment platform designed for creating custom enterprise AI agents and automated workflows. | [.md](https://openaitools.app/tool/mindstudio.md) | | 4 | [Orca](https://openaitools.app/tool/orca) | 1,025,891 | +1% | Free, Open Source, Enterprise on request | Runs parallel CLI coding agents in isolated worktrees, lacking dedicated context compression and cost routing tools. | [.md](https://openaitools.app/tool/orca.md) | | 5 | [Dify](https://openaitools.app/tool/dify-ai) | 819,691 | -15% | Freemium | Open-source visual platform for building LLM apps and agentic workflows, trading Python code for a canvas UI. | [.md](https://openaitools.app/tool/dify-ai.md) | | 6 | [LlamaIndex](https://openaitools.app/tool/llamaindex) | 387,910 | +19.9% | Freemium, Contact for Pricing | Powerful data framework specialized in RAG and document ingestion, but less focused on general agent orchestration loops. | [.md](https://openaitools.app/tool/llamaindex.md) | | 7 | [Augment Code](https://openaitools.app/tool/augment-code) | 326,215 | +24.1% | Freemium, Free Trial, Contact for Pricing | Provides an enterprise context engine for coding agents, but lacks open-source token compression and custom model routing. | [.md](https://openaitools.app/tool/augment-code.md) | | 8 | [Coze](https://openaitools.app/tool/coze) | 177,539 | -33.3% | Freemium | Visual agent development platform for building and publishing autonomous bots without complex backend coding. | [.md](https://openaitools.app/tool/coze.md) | | 9 | [Sim AI](https://openaitools.app/tool/sim-ai) | 140,953 | +20.6% | Freemium, Paid (per user/month), and Enterprise with custom pricing; self-hosting free under Apache 2.0 | Open-source AI workspace providing visual and code-based tools for building, deploying, and governing agent systems. | [.md](https://openaitools.app/tool/sim-ai.md) | | 10 | [Coworker AI](https://openaitools.app/tool/coworker-ai) | 129,346 | -1.8% | Free Trial, Paid, Contact for Pricing | Builds permission-aware context graphs and routes tasks to models, though targeted specifically at enterprise agent workflows. | [.md](https://openaitools.app/tool/coworker-ai.md) | --- Source: https://openaitools.app/compare/agno-vs-caveman More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)