name: Log10 FinOps
description: >
  Financial operations and cost management framework for Log10 LLM logging
  and observability platform. Log10 provides per-model usage tracking and
  cost analytics to help teams understand and optimize spending across
  multiple LLM providers.
url: https://docs.log10.io/observability/model_usage_stats
specificationVersion: "1.0"
framework: FOCUS
costs:
  - name: Platform Subscription
    description: >
      Recurring subscription cost for Log10 platform access. The Free tier
      is available at no cost up to 1 million requests. The Pro and Enterprise
      tiers are priced on a contact-for-pricing basis, typically billed monthly
      or annually.
    type: subscription
    category: SaaS
    currency: USD
    cadence: monthly
    plans:
      - name: Free
        amount: 0
      - name: Pro
        amount: contact-for-pricing
      - name: Enterprise
        amount: contact-for-pricing
  - name: LLM Provider Pass-Through Costs
    description: >
      Log10 itself does not charge per token for LLM inference. Costs for
      underlying LLM calls (OpenAI, Anthropic, Google, Mistral, Meta Llama)
      are billed directly by those providers and passed through transparently.
      Log10 surfaces per-model token usage and cost attribution data to
      support cost allocation and chargeback workflows.
    type: pass-through
    category: Consumption
    currency: USD
    cadence: usage-based
    notes: Billed directly by the upstream LLM provider, not by Log10.
  - name: BigQuery Data Store Integration
    description: >
      Enterprise customers may route log data to Google BigQuery for long-term
      storage and analytics. BigQuery storage and query costs are billed by
      Google Cloud and are not included in Log10 subscription pricing.
    type: pass-through
    category: Storage
    currency: USD
    cadence: usage-based
    plan: Enterprise
costOptimization:
  - name: Per-Model Usage Tracking
    description: >
      Log10's Cost Tracking API and model usage statistics enable teams to
      identify which models, teams, or features are driving the highest LLM
      inference costs, enabling targeted optimization.
    url: https://docs.log10.io/observability/model_usage_stats
  - name: Tag-Based Cost Allocation
    description: >
      Apply tags to logged completions to segment costs by feature, team,
      user cohort, or deployment environment. Enables chargeback and
      showback reporting across organizational units.
    url: https://docs.log10.io/observability/logs
  - name: Model Benchmarking
    description: >
      Use the evaluation and benchmarking API to compare cost versus accuracy
      tradeoffs across LLM providers and model sizes, enabling informed
      decisions on model selection to optimize the cost-accuracy curve.
    url: https://docs.log10.io/feedback/auto_feedback
  - name: AutoFeedback for Accuracy
    description: >
      AutoFeedback replaces expensive human review workflows with AI-generated
      feedback at scale, reducing manual evaluation costs while maintaining
      quality signal for model improvement.
    url: https://docs.log10.io/feedback/auto_feedback
allocation:
  - name: Organization-Level Attribution
    description: >
      All costs and usage are tracked at the organization level using the
      LOG10_ORG_ID. Teams operating shared LLM infrastructure can use tags
      to subdivide usage within a single organization account.
  - name: Enterprise Cost Reporting
    description: >
      Per-model usage reporting with filtering by tags is available to
      enterprise plan users, enabling granular cost attribution and
      reporting aligned with FinOps best practices.
    plan: Enterprise