payment_queryFeeDetails | Enjin RPC Docs

Get a detailed fee breakdown for an extrinsic on Enjin. Analyze base fee, length fee, and adjusted weight fee components to optimize transaction costs for high-volume NFT minting (2,000+ per tx), gaming assets, and cross-chain NFT transfers via Paratoken standard.

Returns a detailed breakdown of the inclusion fee for a given extrinsic on Enjin. While payment_queryInfo returns the total fee as a single value, this method separates it into three components: the fixed base fee, the length-proportional fee, and the weight-based adjusted fee. This granularity is essential for understanding and optimizing transaction costs.

If you provide blockHash, it must be a real chain block hash. Placeholder hashes and stale examples return an unknown Block style error.

Why Enjin? Build on the purpose-built NFT blockchain with protocol-level minting and $100M Metaverse Fund with NFT functions at protocol level, Fuel Tanks for subsidized fees, 700-1000 TPS, 6-second finality, and ERC-1155 standard pioneer.

When to Use This Method

payment_queryFeeDetails is essential for game developers, NFT creators, and enterprises building cross-chain digital assets:

Fee Optimization -- Identify which fee component dominates your transaction cost and optimize accordingly on Enjin
Transaction Cost Analysis -- Build detailed cost breakdowns for high-volume NFT minting (2,000+ per tx), gaming assets, and cross-chain NFT transfers via Paratoken standard, showing users exactly where their fees go
Fee Model Comparison -- Compare fee structures across different extrinsic types or between runtime upgrades that change fee parameters
Batching Decisions -- Determine whether batching calls saves fees by amortizing the base fee across multiple operations

Code Examples

Bash

# Query fee details for an encoded extrinsic
curl -X POST https://enjin-matrix-rpc.n.dwellir.com \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0",
    "method": "payment_queryFeeDetails",
    "params": ["0x2d028400d43593c715fdd31c61141abd04a99fd6822c8558854ccde39a5684e7a56da27d01..."],
    "id": 1
  }'

# Query fee details at a specific block
# Replace 0xYOUR_RECENT_BLOCK_HASH with a recent finalized hash from chain_getFinalizedHead
curl -X POST https://enjin-matrix-rpc.n.dwellir.com \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0",
    "method": "payment_queryFeeDetails",
    "params": [
      "0x2d028400d43593c715fdd31c61141abd04a99fd6822c8558854ccde39a5684e7a56da27d01...",
      "0xYOUR_RECENT_BLOCK_HASH"
    ],
    "id": 1
  }'

Common Use Cases

1. Fee Component Analysis for Optimization

Analyze which fee component dominates to guide optimization strategies:

JavaScript

import { ApiPromise, WsProvider } from '@polkadot/api';

async function analyzeFeeComponents(api, tx) {
  const feeDetails = await api.rpc.payment.queryFeeDetails(tx.toHex());

  if (feeDetails.inclusionFee.isNone) {
    return { feeless: true };
  }

  const fee = feeDetails.inclusionFee.unwrap();
  const base = BigInt(fee.baseFee.toString());
  const len = BigInt(fee.lenFee.toString());
  const weight = BigInt(fee.adjustedWeightFee.toString());
  const total = base + len + weight;

  const analysis = {
    baseFee: { value: base, percentage: Number((base * 10000n) / total) / 100 },
    lenFee: { value: len, percentage: Number((len * 10000n) / total) / 100 },
    weightFee: { value: weight, percentage: Number((weight * 10000n) / total) / 100 },
    total
  };

  // Suggest optimization based on dominant component
  if (analysis.lenFee.percentage > 50) {
    analysis.suggestion = 'Length fee dominates -- reduce call data size or batch smaller calls';
  } else if (analysis.weightFee.percentage > 50) {
    analysis.suggestion = 'Weight fee dominates -- choose lighter runtime operations';
  } else {
    analysis.suggestion = 'Fees are balanced -- batch calls to amortize base fee';
  }

  return analysis;
}

2. Batch vs. Individual Fee Comparison

Compare the cost of batching calls versus submitting them individually:

JavaScript

async function compareBatchVsIndividual(api, calls) {
  // Individual fee total
  let individualTotal = 0n;
  for (const call of calls) {
    const tx = api.tx(call);
    const details = await api.rpc.payment.queryFeeDetails(tx.toHex());
    if (details.inclusionFee.isSome) {
      const fee = details.inclusionFee.unwrap();
      individualTotal += BigInt(fee.baseFee.toString())
        + BigInt(fee.lenFee.toString())
        + BigInt(fee.adjustedWeightFee.toString());
    }
  }

  // Batched fee
  const batchTx = api.tx.utility.batchAll(calls);
  const batchDetails = await api.rpc.payment.queryFeeDetails(batchTx.toHex());
  let batchTotal = 0n;
  if (batchDetails.inclusionFee.isSome) {
    const fee = batchDetails.inclusionFee.unwrap();
    batchTotal = BigInt(fee.baseFee.toString())
      + BigInt(fee.lenFee.toString())
      + BigInt(fee.adjustedWeightFee.toString());
  }

  const savings = individualTotal - batchTotal;
  console.log(`Individual total: ${individualTotal} planck`);
  console.log(`Batch total:      ${batchTotal} planck`);
  console.log(`Savings:          ${savings} planck (${Number((savings * 10000n) / individualTotal) / 100}%)`);

  return { individualTotal, batchTotal, savings };
}

3. Fee Tracking Across Runtime Upgrades

Monitor how fee components change after runtime upgrades to detect regressions:

JavaScript

async function compareFeesBetweenBlocks(api, extrinsicHex, blockHashBefore, blockHashAfter) {
  const [before, after] = await Promise.all([
    api.rpc.payment.queryFeeDetails(extrinsicHex, blockHashBefore),
    api.rpc.payment.queryFeeDetails(extrinsicHex, blockHashAfter)
  ]);

  function extractFees(details) {
    if (details.inclusionFee.isNone) return null;
    const fee = details.inclusionFee.unwrap();
    return {
      base: BigInt(fee.baseFee.toString()),
      len: BigInt(fee.lenFee.toString()),
      weight: BigInt(fee.adjustedWeightFee.toString())
    };
  }

  const feesBefore = extractFees(before);
  const feesAfter = extractFees(after);

  if (feesBefore && feesAfter) {
    console.log('Fee comparison:');
    console.log(`  Base fee:   ${feesBefore.base} -> ${feesAfter.base}`);
    console.log(`  Length fee: ${feesBefore.len} -> ${feesAfter.len}`);
    console.log(`  Weight fee: ${feesBefore.weight} -> ${feesAfter.weight}`);
  }
}

Fee Components Explained

Component	Source	How It's Calculated	Optimization Strategy
baseFee	`ExtrinsicBaseWeight`	Fixed cost per extrinsic defined by the runtime	Batch multiple calls into a single extrinsic to pay only one base fee
lenFee	`TransactionByteFee`	`encodedLength × lengthToFee` coefficient	Minimize encoded extrinsic size by using compact encodings and avoiding large payloads
adjustedWeightFee	`WeightToFee`	Execution weight multiplied by the fee multiplier, which adjusts based on block fullness	Choose lighter operations, submit during low-traffic periods when the multiplier is lower

Tip multiplier: The adjustedWeightFee is sensitive to network congestion. When blocks are consistently more than half full, the fee multiplier increases, raising the weight fee. During low-traffic periods, the multiplier decreases toward its minimum.

Error Handling

Common errors and solutions:

Error Code	Description	Solution
-32602	Invalid params	Ensure the extrinsic hex string is properly SCALE-encoded with the `0x` prefix
-32603	Internal error	The runtime could not compute fees -- verify the extrinsic is valid for the target block
-32005	Rate limit exceeded	Reduce request frequency or implement client-side rate limiting
Null inclusionFee	Feeless extrinsic	Inherent extrinsics and some unsigned extrinsics do not pay fees -- this is expected behavior

payment_queryInfo -- Get the total fee and execution weight for an extrinsic as a single value
state_call -- Call TransactionPaymentApi_query_fee_details directly for more control
system_properties -- Get token decimals and symbol for human-readable fee display
author_submitExtrinsic -- Submit the extrinsic after confirming acceptable fees
author_submitAndWatchExtrinsic -- Submit and track the extrinsic through finalization

payment_queryFeeDetails - Enjin RPC Method

When to Use This Method

Code Examples

Common Use Cases

1. Fee Component Analysis for Optimization

2. Batch vs. Individual Fee Comparison

3. Fee Tracking Across Runtime Upgrades

Fee Components Explained

Error Handling

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