Cardano has over 30 network parameters–the mechanisms that control how the Cardano Blockchain works. In this installment of our ongoing exploration of Cardano’s network parameters, we turn our attention to price_step, one half of the critical executionPrices configuration that determines how much users pay for smart contract operations. While its partner price_mem governs the cost of memory usage, price_step sets the price for computational processing power—every logical operation, cryptographic calculation, and algorithmic step executed by Plutus scripts. As of December 2025, the current value is 721/10,000,000 lovelace per execution step.
What is it
The price_step parameter establishes the cost per CPU execution step in Plutus smart contracts. Unlike simple ADA transfers that require minimal computational overhead, smart contract transactions demand significant processing power to execute complex business logic, validate cryptographic proofs, or perform mathematical calculations across decentralized applications.
Fun fact: the fact that calculations are done at the Plutus low level code layer, does not mean you need to write your code in Haskell or Plinth. In Cardano there are developer tooling that lets you write smart contracts in, Haskell, Aiken (a rust/elm like language), typescript, python, and even C#. Your higher level language code will be compiled to Plutus IR (like LLVM for Apple iOS apps or Rust programs). From Plutus IR, the code is turned into typed-Plutus core. This is just before the raw 1s and 0s.
This parameter works as an economic mechanism, ensuring that computational resources are allocated efficiently while preventing spam attacks that could overwhelm the network with expensive operations. Every time you interact with a DeFi protocol, participate in a multi-signature transaction, or execute complex validation logic, the CPU steps required by these operations are multiplied by this price to determine part of your transaction fee.
How does it work?
Like all execution unit pricing in Cardano, price_step doesn’t measure actual CPU cycles on physical hardware. Instead, Cardano abstracts computational work into deterministic “execution steps” defined by the Plutus cost models. These steps normalize real-world operations—like hash computations, signature verifications, or conditional branches—into standardized costs that apply equally across the decentralized network.
This abstraction serves several critical purposes:
Deterministic execution: The same script operation always consumes the same number of steps, regardless of the hardware running it. A cryptographic hash operation costs exactly the same whether executed on a high-end server or modest home computer.
Fair pricing: Transaction fees scale predictably with computational complexity. More processing-intensive operations pay proportionally higher fees via the price_step multiplier.
Network protection: By pricing computational resources, the network prevents actors from submitting transactions that would consume excessive CPU resources, maintaining consistent block validation times across all nodes.
The current pricing structure means each execution step costs 0.0000721 lovelace (721/10,000,000). For perspective, a typical DeFi swap might consume 500,000 to 1,500,000 steps, translating to roughly 36-108 lovelace in CPU costs alone—before adding memory, transaction size, and base fees.
Why you might care
For DApp developers, price_step directly impacts the economics of your smart contracts. Scripts that perform heavy computations, complex cryptographic operations, or iterate through large datasets will accumulate substantial step costs. This constraint encourages efficient programming patterns such as:
Algorithmic optimization: Choose algorithms that minimize computational steps rather than simply focusing on code readability or convenience.
Off-chain computation: Move expensive calculations off-chain when possible, validating results on-chain rather than performing the full computation.
Batch operations: Combine multiple operations into single transactions to amortize fixed costs across more work.
For users, understanding price_step helps explain why certain DApp interactions cost more than others. A simple token transfer might require minimal steps, while complex DeFi strategies involving multiple protocols, oracle price feeds, and mathematical calculations will naturally incur higher fees due to their computational demands.
The parameter also reflects Cardano’s broader economic philosophy: computational resources should be priced fairly based on actual consumption rather than arbitrary gas markets or auction mechanisms. This creates more predictable fee structures for businesses, developers and end users.
The bigger picture
price_step represents one half of Cardano’s dual-resource model for smart contract pricing. Together with price_mem (which prices memory allocation), these parameters create a comprehensive cost structure that accounts for both the time complexity (CPU) and space complexity (memory) of blockchain computations.
This approach differs from simpler gas models used by blockchains like Ethereum, where a single metric attempts to capture all resource usage. By separating CPU and memory costs, Cardano can more accurately price different types of operations—memory-intensive data processing versus CPU-heavy cryptographic work—leading to fairer resource allocation across diverse use cases.
As Cardano’s smart contract ecosystem evolves and network usage patterns change, price_step may be adjusted through the built in on-chain governance votes to maintain optimal economic incentives. These adjustments balance multiple considerations: keeping transaction costs reasonable for users, ensuring fair compensation for node operators, and maintaining network security against resource exhaustion attacks.
Understanding price_step isn’t just about grasping a technical parameter—it’s about understanding how Cardano creates sustainable economics for decentralized computation, ensuring the network can scale efficiently while serving diverse applications from simple payments to complex financial instruments.
Noch keine Kommentare...