Aragon Gas Cost Documentation 🦅⛽

Users (including myself) have often asked how much it costs to deploy a DAO or how much it costs to perform actions within a DAO (such as voting). While the USD price of these actions fluctuates with the Ethereum gas market, the ETH price does not.

Documenting the gas costs for Aragon DAO template and application operations would help users understand the initial upfront costs of deploying an Aragon DAO, as well as the ongoing costs of using it. Users could then compare this cost to traditional models, such as using an LLC, to understand if Aragon is the best choice for them (and it should be!).

We can take immediate action on this. There are lots of Aragon DAO templates and apps that people use, but don’t know the cost of until they are ready to sign a tx. We can change that by running tests provided by the solidity-coverage package and estimating the gas costs. The scope of applications and templates to be checked will include, but not be limited to:

  • All Aragon apps published to mainnet
  • All Aragon DAO templates published to mainnet

I strongly encourage someone to adopt this proposal by suggesting a fair price for the scope of work. If we can achieve rough consensus on the price and scope of work, then the CFDAO should support this :slight_smile:


If the scope is limited to profiling the apps and templates on mainnet then this is something that can be done in a day. 200 DAI seems reasonable to me. Ive got some free time towards the end of the week and I’ll be happy to do it


Awesome! That feels like a very reasonable ask that would greatly enhance onboarding for new users. Submit a CFDAO proposal and I’ll support it :slight_smile:

Hi Aaron, Any progress on this?

I am new to Aragon and I think it is an important question to reply to and document, also the cost for ongoing operations, such as voting, even if it is approximated…

I do not know how to help respond this at this time, but would be glad to take pointers to help with this documentation.


To retrieve past and present gas prices, visit YCharts or Etherscan.

To predict future gas prices, solve time series forecasting using machine learning models.