LLM Price Wars: Find the Cheapest AI for Your Use Case

Prices are calculated based on each provider's published per-token API pricing. Monthly cost = (daily requests x 30) x (average input tokens x input price + average output tokens x output price) / 1,000,000. These are raw API costs and don't include platform fees or volume discounts.

For most production chatbots, Claude Sonnet 4 or GPT-4o offer the best balance of quality, speed, and cost. If you need the absolute cheapest option with acceptable quality, GPT-4o-mini or Gemini 2.5 Flash are excellent. For high-stakes conversations, Claude Opus 4 provides the best reasoning quality.

Llama 3.3 70B appears cheap at API pricing, but self-hosting requires GPU infrastructure (A100/H100 instances). At low volumes, API services are almost always cheaper. Self-hosting becomes cost-effective above ~50M tokens/day when you can keep GPUs at high utilization.

The biggest levers: 1) Use prompt caching (saves 50-90% on repeated prefixes). 2) Route simple tasks to cheaper models with a model router. 3) Optimize prompts to use fewer tokens. 4) Batch non-urgent requests. 5) Cache frequent responses. Most teams can cut costs 60-80% with these techniques.

Yes, LLM pricing has been dropping steadily. Prices have fallen roughly 90% over the past two years. We update this calculator regularly, but always verify current pricing on each provider's website before making budget commitments.

Most providers impose rate limits (requests/minute) and daily quotas, especially on cheaper tiers. High-volume users need to factor in enterprise plans or negotiate custom limits. This calculator focuses on per-token costs, not rate limit constraints.