Comparisons / AutoGPT vs Eve
AutoGPT vs Eve: Which Agent Framework to Use?
AutoGPT vs Eve, head to head
AutoGPT and Eve both let you build an agent, but they sit in different parts of the stack and they assume different things about who's writing the code.
AutoGPT was one of the first autonomous agent projects, spawning 165k+ GitHub stars.
Eve is Vercel's open-source TypeScript agent framework, launched June 17 2026.
Underneath, both wrap the same thing: a model call, a tool dispatch, a loop. The decision is about which abstraction your team wants to think in day to day, and which ecosystem you're willing to inherit along with it. There's an honest, framework-free version of the same pattern in about 60 lines of Python in the lesson at the bottom of this page — useful as a baseline regardless of which framework wins.
Pick AutoGPT if
Pick AutoGPT if autoGPT pioneered the autonomous agent pattern, but most of its complexity comes from managing an unbounded loop — not from the core agent logic. For bounded tasks, a plain while loop with tool dispatch gives you the same capability with full control over when to stop. The tradeoffs in its intro should match how your team already thinks about agents; Eve will feel like translation if they don't.
Pick Eve if
Pick Eve if eve earns its keep when you want durable execution, sandboxed code exec, and multi-model routing without wiring three separate services. If you're already on Vercel, it composes; if not, the runtime pieces are the value and they don't travel. For a single-loop tool-using agent, plain TypeScript ships faster. The tradeoffs in its intro should match how your team already thinks about agents; AutoGPT will feel like translation if they don't.
By the numbers
By the numbers
AutoGPT
183.1k
46.2k
Python
MIT
2023-03-16
Toran Bruce Richards
Eve
3.5k
180
TypeScript
Apache-2.0
2026-06-17
Vercel
Vercel (public)
Runs on Vercel Sandbox + AI Gateway; deploys anywhere Node runs
Yes
GitHub stats as of April 2026. Stars indicate community interest, not necessarily quality or fit for your use case.
| Concept | AutoGPT | Eve |
|---|---|---|
| Agent | AutoGPT `Agent` class with goal decomposition and self-prompting loop | A directory with `agent.ts` + `instructions.md` + subfolders — the framework wires them together |
| Tools | Plugin system with web browsing, file I/O, code execution, Google search | Each file in `tools/` exports one tool; schema comes from a Zod export |
| Agent Loop | Autonomous loop: think → plan → act → observe → repeat until goal met | — |
| Memory | Vector DB (Pinecone/local) for long-term memory, message history for short-term | — |
| Planning | GPT-4 generates multi-step plans, stores in task queue, revises on failure | — |
| Self-Critique | Built-in self-evaluation prompt that critiques each action before executing | — |
| Durability | — | Vercel Workflow SDK checkpoints every step so a crashed agent resumes where it left off |
| Sub-agents | — | Each `subagents/*.ts` becomes a callable sub-agent the parent can hand off to |
| Sandboxed exec | — | Vercel Sandbox runs untrusted code in isolated micro-VMs, one API call away |
| Schedules | — | `schedules/*.ts` exports a cron expression + handler; Vercel runs it |
Or build your own in 60 lines
Both AutoGPT and Eve implement the same 8 patterns. An agent is a function. Tools are a dict. The loop is a while loop. The whole thing composes in ~60 lines of Python.
No framework. No dependencies. No opinions. Just the code.
Build it from scratch →