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What is Price Per Token?

Price Per Token is a free LLM API pricing comparison tool that aggregates and compares the costs of large language models from over 300 sources across 30+ providers, including major players like OpenAI, Anthropic, Google, and emerging alternatives like DeepSeek. The platform provides real-time pricing data for input and output tokens, helping developers, AI engineers, and product managers make informed decisions about which language models offer the best value for their specific use cases. With daily updates pulled directly from official sources, users can track how pricing evolves across the industry and calculate the exact costs of their API usage before committing to a particular provider. This is particularly valuable in the rapidly changing AI space where pricing strategies and model capabilities shift frequently.

Key Features

Real-time pricing comparison

Compare token costs (input/output) across 300+ models from 30+ providers, updated daily

Multi-provider coverage

Includes OpenAI (GPT-4, GPT-5), Anthropic (Claude), Google (Gemini), and 30+ additional providers

Cost calculator

Estimate API expenses based on your expected token usage and model selection

Historical pricing tracking

Monitor how model pricing changes over time to identify trends

Model filtering and sorting

Search by provider, capability, pricing tier, or performance metrics

Official data integration

Pricing pulled directly from provider APIs and official documentation

Pros & Cons

Advantages

  • Completely free to use with no registration or paywalls for core features
  • thorough coverage of major and emerging LLM providers in one place
  • Daily updates ensure pricing information stays current in a fast-moving market
  • Simple, intuitive interface makes price comparison quick and accessible
  • Helps prevent vendor lock-in by making cost comparisons transparent and effortless

Limitations

  • May not include every niche or newly-launched provider immediately due to coverage gaps
  • Does not account for volume discounts, enterprise agreements, or custom pricing arrangements
  • Pricing data is only useful for token costs; doesn't compare latency, availability, or model quality

Use Cases

Developers choosing which LLM API to integrate into a new application based on budget constraints

ML engineers evaluating cost-benefit tradeoffs when selecting between multiple capable models

Startup founders optimising API spending to reduce operational costs during scaling

DevOps teams monitoring provider pricing changes to catch cost increases or opportunities for savings

Product managers assessing whether switching to a cheaper alternative model is viable for their product