The Solana Fee Tracker monitors live priority fee data on Solana Mainnet, providing real-time visibility into current network costs across multiple fee percentiles. Use this resource to make informed decisions about your priority fee settings before submitting transactions.

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Priority fee data represents the compute unit price in microLamports per CU. Low percentiles reflect minimum fees for basic inclusion; high percentiles indicate competitive fees for fast confirmation during congestion.

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Understanding Fee Percentiles

Fee tracker data is organized into percentile buckets from recent Solana blocks. The 25th percentile (Low) reflects fees paid by transactions at the lower end of the fee market — suitable for non-urgent activity. The 50th percentile (Median) represents the midpoint of all fees paid in recent blocks and is the recommended starting point for most applications. The 75th percentile (High) and 95th percentile (Very High) reflect fees paid by time-sensitive transactions competing for fast block inclusion.

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Real-Time vs. Historical Fee Data

Fee data streams are updated every few seconds using Solana RPC node data, typically covering the past 150 blocks (approximately 60 seconds of Solana history given ~400ms block times). For applications requiring even more granular fee market intelligence, providers like Triton One, QuickNode, and Helius offer dedicated priority fee streaming APIs with sub-second update intervals and account-level fee granularity.

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How to Use Fee Tracker Data

When building a trading bot or high-frequency application, poll the fee tracker API at regular intervals and cache the latest percentile values. Before submitting each transaction, select the appropriate percentile based on urgency: use Medium for routine operations, High for actively managed positions, and Very High for arbitrage or MEV scenarios. Implementing an exponential backoff fee escalation strategy — starting at Medium and escalating to High or Very High on retry — is a robust pattern that balances cost efficiency with confirmation reliability.