Comparisons / CAMEL AI vs Eve
CAMEL AI vs Eve: Which Agent Framework to Use?
CAMEL AI vs Eve, head to head
CAMEL AI 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.
CAMEL AI pioneered role-playing multi-agent conversations in a 2023 NeurIPS paper.
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 CAMEL AI if
Pick CAMEL AI if cAMEL AI's research contribution — role-playing and inception prompting — is a genuinely useful technique for reducing hallucination through multi-agent debate. But the technique is the value, not the framework. Two LLM calls with different system prompts give you the same pattern in plain Python. 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; CAMEL AI will feel like translation if they don't.
By the numbers
By the numbers
CAMEL AI
16.6k
1.9k
Python
Apache-2.0
2023-03-17
CAMEL-AI.org (King Abdullah University)
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 | CAMEL AI | Eve |
|---|---|---|
| Agent | `ChatAgent` with `role_name`, `role_type`, and `system_message` for behavior | A directory with `agent.ts` + `instructions.md` + subfolders — the framework wires them together |
| Tools | Tool modules registered on agents with OpenAI-compatible function schemas | Each file in `tools/` exports one tool; schema comes from a Zod export |
| Role-Playing | `RolePlaying` session with `user_agent`, `assistant_agent`, and inception prompting | — |
| Inception Prompting | System prompts that embed the task, roles, and constraints to prevent drift | — |
| Society | Multi-agent societies with role assignment, communication, and voting | — |
| Task Decomposition | AI Society that splits tasks into subtasks assigned to specialist role pairs | — |
| 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 CAMEL AI 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 →