CentML · FinOps Profile

Centml Finops

FinOps view of CentML spend. CentML bills on a credit-based model where 1 credit equals 1 USD. Serverless inference is metered by input and output tokens with per-token rates that vary by model. Dedicated deployments are metered by GPU hardware type and duration on a per-minute basis (per-GPU-hour equivalent). Exact per-model and per-GPU-hour rates are not reconciled here.

Centml Finops is the FinOps profile for CentML on the APIs.io network, aligned with the FinOps Foundation Framework.

It defines 4 billable meters, billed in USD, on a monthly cycle, and pricing category usage-based.

The profile maps 8 FOCUS columns for cost-allocation reporting.

Tagged areas include AI, LLM, Inference, Serverless, and GPU.

Category: AI and Machine Learning Pricing: Usage-Based Billing: Monthly FOCUS v1.3
AILLMInferenceServerlessGPUFinOpsCost ManagementFOCUS

Framework Alignment

Framework
Data Spec

Charge Categories

UsagePurchaseAdjustment

FOCUS Columns

BillingCurrency
USD
ChargeCategory
Usage
InvoiceIssuerName
CentML
PricingCategory
Usage-Based
ProviderName
CentML
PublisherName
CentML
ServiceCategory
AI and Machine Learning
ServiceName
CentML Platform

Meters

serverless_input_tokens
Unit: tokens
Input tokens sent to serverless chat / text completions, billed per 1M tokens per model.
serverless_output_tokens
Unit: tokens
Output tokens generated by serverless endpoints, billed per 1M tokens per model.
dedicated_gpu_hours
Unit: gpu_hours
GPU hours consumed by dedicated inference / compute deployments, billed per minute by hardware instance type.
credits
Unit: credits
CentML credits consumed, where 1 credit equals 1 USD.

Sources