Transaction Fee Analysis
In this post, we analyze actual transaction fees across 6 different chains to help developers understand the real costs of running their applications
Understanding Transaction Fees
When building applications on blockchain, transaction fees can significantly impact both user experience and operational costs. Whether you're building a payment system, a gaming platform, or a DeFi protocol, understanding the true cost of transactions is essential.
Transaction fees are payments made to execute operations on a blockchain network. These fees compensate validators and miners for:
- Computational resources: Processing and executing your transaction
- Storage: Recording transaction data permanently on the blockchain
- Network bandwidth: Broadcasting your transaction across the network
- Security: Preventing spam and abuse by making operations cost something
Transaction fees vary widely across blockchains due to:
- Network Congestion: Higher demand typically leads to higher fees
- Consensus Mechanism: Different mechanisms have different computational costs
- Token Economics: The native token price directly affects USD-denominated fees
- Fee Models: Fixed fees vs. gas-based pricing
How Transaction Fees Are Calculated
Each blockchain has its own fee calculation mechanism:
NEAR Protocol
NEAR uses a gas-based system where fees are calculated as:
Fee = Gas Units Used × Gas Price (in NEAR)
Gas units are determined by the computational complexity of operations (transaction processing, function calls, storage). The gas price is fixed at 0.0001 NEAR per gas unit, making fees predictable and stable.
Aptos
Aptos implements a gas system similar to Ethereum where:
Fee = Gas Units × Gas Price (in Octas, where 1 APT = 100,000,000 Octas)
The gas price is dynamic and adjusts based on network demand, with a minimum gas price to prevent spam.
Arbitrum
As an Ethereum Layer 2, Arbitrum's fees consist of:
Fee = L2 Gas Used × L2 Gas Price + L1 Data Fee
The L2 component covers Arbitrum computation, while the L1 data fee covers the cost of posting transaction data to Ethereum mainnet.
Ethereum
Ethereum uses EIP-1559 gas model:
Fee = Gas Units × (Base Fee + Priority Fee)
The base fee is burned and adjusts based on network congestion. The priority fee (tip) goes to validators and incentivizes transaction inclusion.
Solana
Solana uses a simple fee structure with:
Fee = Number of Signatures × Lamports per Signature (5,000 lamports)
Where 1 SOL = 1,000,000,000 lamports. Most transactions have one signature, resulting in a fixed ~0.000005 SOL fee.
Sui
Sui uses a gas-based system where:
Fee = Computation Units × Gas Price (in MIST, where 1 SUI = 1,000,000,000 MIST)
The gas price fluctuates based on network load, with validators setting minimum prices through a gas price mechanism.
What Actions Affect Transaction Fees?
While our benchmark focuses on simple token transfers, transaction fees can vary significantly based on the operations performed:
Computational Complexity
- Simple transfers: Minimal computation, lowest fees
- Smart contract calls: Higher fees based on function complexity
- Cross-contract calls: Multiple contract interactions increase fees
- Complex calculations: More CPU-intensive operations cost more gas
Storage Operations
- Reading data: Generally cheaper or free
- Writing data: Storing new data on-chain is expensive
- Updating state: Modifying existing storage incurs fees
- Deleting data: Some chains offer gas refunds for freeing storage
Transaction Size
- Data payload: Larger transaction data increases fees
- Function arguments: More parameters = higher costs
- Return values: Larger outputs can affect fees
Network-Specific Factors
- NEAR: Storage staking requires locking tokens proportional to data stored
- Ethereum/Arbitrum: Contract deployment costs significantly more than transfers
- Solana: Additional signatures (multi-sig) multiply the base fee
- Aptos/Sui: Complex Move bytecode execution increases gas consumption
The fees measured in our benchmark represent the baseline cost for the simplest possible operation. Real-world application transactions typically cost 2-100x more depending on complexity.
Real-World Fee Analysis
To ensure fair comparison, we:
- Performed simple native token transfers to avoid smart contract complexity variations
- Used public RPC endpoints
- Collected 28-30 transactions per blockchain
- Calculated transaction fees using:
transactionFee = balanceBefore - balanceAfter - amount - Converted fees to USD at current market prices
Results
Here is a summary of the average transaction fees observed:
Mainnet:
| Blockchain | Avg Fee (Native) | Avg Fee (USD) | Token Price | Fee Documentation |
|---|---|---|---|---|
| Arbitrum | 0.00000021 | $0.000000042 | $0.20 | Docs |
| Aptos | 0.000012 | $0.000019 | $1.59 | Docs |
| Ethereum Sepolia | 0.000000021 | $0.000062 | $2,944.00 | Docs |
| NEAR | 0.000045 | $0.000070 | $1.56 | Docs |
| Solana | 0.0000050 | $0.000645 | $129.00 | Docs |
| Sui | 0.0015028 | $0.002239172 | $1.49 | Docs |
Testnet:
| Blockchain | Avg Fee (Native) | Avg Fee (USD) | Token Price | Fee Documentation |
|---|---|---|---|---|
| Arbitrum | 0.00000042 | $0.000000084 | $0.20 | Docs |
| Aptos | 0.000012 | $0.000019 | $1.59 | Docs |
| Ethereum Sepolia | 0.000000021 | $0.000062 | $2,944.00 | Docs |
| NEAR | 0.000045 | $0.000070 | $1.56 | Docs |
| Solana | 0.0000050 | $0.000645 | $129.00 | Docs |
| Sui | 0.001965 | $0.002928 | $1.49 | Docs |
Resources
The complete fee analysis data and tools are open source and available on GitHub:
- Benchmark Data: matiasbenary/benchmarks - Raw fee data and analysis
- Network Analyzer: matiasbenary/networksAnalizer - Tool used to measure and analyze fees across different networks
Want to build on NEAR with low transaction costs? Check out our developer documentation to get started.