The genai_input_cost function calculates the cost of input tokens (prompt tokens) for a GenAI API call based on the model name and number of input tokens. This helps you understand and track the cost of prompts separately from responses.

You can use this function to analyze prompt costs, optimize prompt engineering for cost efficiency, track input spending separately, or create detailed cost breakdowns.

For users of other query languages

If you come from other query languages, this section explains how to adjust your existing queries to achieve the same results in APL.

In Splunk SPL, you would need to lookup pricing and calculate costs manually.

```sql Splunk example | lookup model_pricing model OUTPUT input_price | eval input_cost=(input_tokens * input_price / 1000000) ```
['ai-logs']
| extend input_cost = genai_input_cost(model, input_tokens)

In ANSI SQL, you would join with a pricing table and calculate input costs.

```sql SQL example SELECT l.*, (l.input_tokens * p.input_price / 1000000) as input_cost FROM ai_logs l JOIN model_pricing p ON l.model = p.model_name ```
['ai-logs']
| extend input_cost = genai_input_cost(model, input_tokens)

Usage

Syntax

genai_input_cost(model, input_tokens)

Parameters

Name Type Required Description
model string Yes The name of the AI model (for example, 'gpt-4', 'claude-3-opus', 'gpt-3.5-turbo').
input_tokens long Yes The number of input tokens (prompt tokens) used in the API call.

Returns

Returns a real number representing the cost in dollars (USD) for the input tokens based on the model's pricing.

Example

Calculate the cost of input tokens for a GenAI chat operation.

Query

['otel-demo-genai']
| extend model = ['attributes.gen_ai.request.model']
| extend input_tokens = tolong(['attributes.gen_ai.usage.input_tokens'])
| extend input_cost = genai_input_cost(model, input_tokens)
| summarize total_input_cost = sum(input_cost), avg_input_cost = avg(input_cost)

Run in Playground

Output

total_input_cost avg_input_cost
45.67 0.0187

This query calculates the total and average cost of input tokens, helping you understand prompt spending patterns.

  • genai_output_cost: Calculates output token cost. Use this alongside input costs to understand the full cost breakdown.
  • genai_cost: Calculates total cost (input + output). Use this when you need combined costs.
  • genai_get_pricing: Gets pricing information. Use this to understand the pricing structure behind cost calculations.
  • genai_estimate_tokens: Estimates token count from text. Combine with input cost to predict prompt costs before API calls.

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