genai_input_cost

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

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.

Other query languages#

Splunk SPL users

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

Splunk example

| lookup model_pricing model OUTPUT input_price
| eval input_cost=(input_tokens * input_price / 1000000)

APL equivalent

['ai-logs']
| extend input_cost = genai_input_cost(model, input_tokens)

ANSI SQL users

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

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