cost_models (Plutus Script Execution Costs)

In this installment, we will be looking at Cardano’s cost_model parameter.

Any sophisticated computing system needs precise rules to manage resource allocation. Think about it – processing power, storage, and time are all valuable resources. They must be doled out fairly, and in a way that allows the system to work for everyone.

Blockchain networks are no different. Consider these questions:

• What should happen when someone submits a smart contract that is written in a way that it could consume unlimited resources?
• How do you ensure the network remains stable while still allowing complex decentralized applications to flourish?

Here is an answer: One effective mechanism to control and manage resource allocation on a blockchain is transaction price.

These questions –and this answer– about resource management and fair pricing are at the core of the cost_model parameter, also known as cost_model Parameters for Plutus script execution.

What are cost_model Parameters?

In Cardano, the cost_model parameter defines the computational cost of executing Plutus smart contracts on the blockchain.

Every operation within a Plutus script—from basic arithmetic to complex data manipulations—consumes computational resources that must be accounted for and limited in order to prevent network abuse. The cost_model parameters establish the precise “price” in “execution units” for each type of operation that a Plutus script can perform.

Mathematically, each Plutus builtin function has an associated cost_model that defines how much “CPU” and “memory” execution units it consumes based on its inputs. For example, adding two integers might cost 100 CPU units, while performing cryptographic operations could cost several thousand units depending on the size and complexity of the operation.

The cost_model serves as Cardano’s resource metering system for smart contracts. When a transaction includes a Plutus script, the network calculates the total execution cost by summing up the costs of all individual operations performed. This total cost is then compared against predefined limits to ensure the script doesn’t consume excessive resources that could slow down or destabilize the network.

The outcome of the cost_model calculation can go two ways:

• If the size of the operation is within accepted limits, the transaction can be processed – with an appropriately scaled transaction fee to fairly cover processing costs.
• If the size of the operation exceeds a limit, or if the code is faulty in a way that could consume excess resources, the transaction will not be allowed. No transaction fee is high enough to risk destabilizing the network!

Why Do cost_model Parameters Matter?

The careful calibration of this parameter is one of the main reasons why the cost to run something on Cardano is predictable, efficient and secure.

Network Security & Stability: Properly set cost_model parameters prevent denial-of-service attacks where malicious actors could submit resource-intensive scripts designed to overload validators. By accurately pricing computational operations, the network can reject scripts that would consume excessive resources.

Economic Efficiency: cost_model ensures that transaction fees reflect the actual computational burden of smart contract execution. Users pay proportionally for the resources they consume, creating a fair and sustainable economic model for the network.

Developer Experience: Well-calibrated cost_model enables developers to predict and optimize the execution costs of their smart contracts. This predictability is crucial for building economically viable dApps and planning the cost of creating transactions.

Innovation Enablement: Accurate cost_modeling allows more complex smart contracts to execute within reasonable resource limits, enabling sophisticated DeFi protocols, NFT marketplaces, and other advanced applications.

How are cost_model Parameters Determined?

cost_model parameters are derived through extensive benchmarking and empirical testing of Plutus Core operations. The process involves running thousands of test cases with varying input sizes to determine the actual computational cost of each builtin function on reference hardware.

The Cardano development teams use sophisticated profiling tools to measure CPU cycles, memory usage, and execution time for each Plutus primitive. This data is then analyzed to create mathematical models that can predict the cost of any operation based on its input parameters.

Since Cardano’s big Hard Fork upgrade (the Plomin upgrade), the cost_model and the rest of the parameters can be set through Cardano’s governance process. The community of Delegated Representatives (DReps) can vote on proposals to update the cost_model parameter as the understanding of actual execution costs improves or as the underlying Plutus interpreter becomes more efficient.

Real-World Impact: cost_model in Action

The effects of cost_model parameters are visible every time a Plutus script executes on Cardano. Consider a decentralized exchange (DEX) swap transaction: the cost_model determines how much execution budget is needed for operations like validating signatures, checking token balances, calculating swap ratios, and updating the liquidity pool state.

When Project Catalyst funds developers building complex dApps, the cost_model parameter directly influences their development decisions. A carefully optimized cost_model enables developers to build more sophisticated applications within the same execution budget, fostering innovation while maintaining network security.

DeFi protocols rely on predictable execution costs to ensure their operations remain economically viable. NFT marketplaces need accurate cost_modeling for batch minting and complex royalty calculations. Gaming applications depend on an efficient cost_model for managing large amounts of game state and complex rule validation that are stored on the blockchain.

Challenges and Considerations

While cost_model parameters are essential for network security and efficiency, they present several challenges:

Benchmarking Accuracy
cost_model must accurately reflect real-world execution costs across diverse hardware configurations. Underestimating costs could lead to network instability, while overestimating costs unnecessarily limits smart contract capabilities. The challenge lies in creating models that are both accurate and conservative enough to handle edge cases.

Balancing Performance and Security
There’s an inherent tension between allowing powerful smart contracts and preventing resource abuse. cost_model must be restrictive enough to prevent attacks while permissive enough to enable meaningful applications. Finding this balance requires continuous refinement as the ecosystem evolves and new computer hardware is developed.

Evolution and Updates
As the Plutus interpreter becomes more efficient or new builtin functions are added, cost_model must be updated accordingly. However, changes to cost_model can break existing applications that were designed around specific execution cost assumptions, requiring careful coordination and update strategies.

Hardware Diversity
Cardano validators run on diverse hardware configurations, from powerful servers to modest consumer devices. cost_model must account for this diversity to ensure consistent performance across all validators while not being overly conservative