> For the complete documentation index, see [llms.txt](https://gmgm-market.gitbook.io/gmgm-market/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://gmgm-market.gitbook.io/gmgm-market/solver-excitation.md).

# Solver excitation

In all intent-based systems, solvers need incentives to cover their operating costs and make a profit. To gain incentives, solvers need to compete with other third-party solvers as well as generic MEV bots that run front-running tactics such as sandwich attacks. The solvers themselves are part of the MEV ecosystem as they try to extract the maximum value from each intent they solve. The optimized solver stimulus design works by aligning the solver stimulus with the best user results, so more MEV for the solver actually results in faster and better execution for the user.

GMGM Market adapts to any solver excitation design, and we use the fee auto-sharing incentive formula. In this case, the fees are all charged from the tokens involved in the intent, and the user does not have to hold GAS tokens or pay gas directly at a later stage.

Automatic incentives are used in our exchanges. For users to execute swaps on the origination demand, if the solver finds a liquidity source route, they can get additional tiered fees to cover the transaction gas cost and earn profits. Solvers scramble to find the best route they can perform. Users only need to specify the required inputs and outputs, but they don't need to sign off on explicit fees.