Lamini · FinOps Profile

Lamini Finops

FinOps view of Lamini Platform spend. On the On-Demand tier, Lamini bills a flat per-token inference rate and a per-tuning-step rate, drawing down prepaid or free credit. Enterprise spend is a negotiated contract for reserved or on-premises GPU capacity. The two primary cost drivers are inference token volume and tuning steps (which scale with dataset size, epochs, and GPU count).

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

It defines 5 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, Fine-Tuning, Memory Tuning, and Inference.

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

Framework Alignment

Framework
FinOps Foundation Framework
Data Spec
FOCUS v1.3

Charge Categories

UsagePurchaseAdjustment

FOCUS Columns

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

Meters

inference_tokens
Unit: tokens
Tokens generated and consumed via /v1/completions, billed at a flat per-1M-token rate.
tuning_steps
Unit: steps
Tuning steps executed by /v1/train jobs, billed per step and scaling with dataset size, epochs, and GPU count.
embedding_requests
Unit: requests
Embedding generation requests via /v1/embedding.
classification_requests
Unit: requests
Classification and prediction requests via the /v1/classifier endpoints.
free_credit
Unit: usd
Free credit granted to new accounts, drawn down before paid usage.

Sources

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