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Free LLM & API Cost Calculators 2026 | APICalculators
APICalculators · 2026-06-14 · via Show HN

LLM Token & API Cost Calculator

Estimate monthly spend across GPT-5.5, GPT-5.4 nano, Claude Sonnet 4.6, and Gemini 3.5 Flash based on your token throughput.

Pricing reflects published 2026 public API rates (USD, pay-as-you-go). Volume discounts, cached input, and batch pricing are not applied. Verify against the provider's pricing page before budgeting.

LLM Cost Calculator — GPT-5.5, GPT-5.4 Nano & Gemini 3.5 Flash Pricing

This LLM cost calculator helps developers and product teams estimate their monthly OpenAI, Anthropic, and Google API spend before it hits their credit card. You enter three variables — input tokens per request, output tokens per request, and monthly request volume — and the tool computes your total cost using current June 2026 USD pricing. GPT-5.5 costs $5.00 per million input tokens and $30 per million output tokens. For budget workloads, GPT-5.4 nano at $0.20/$1.25 per 1M is the most affordable OpenAI option in 2026 — a team running 100,000 requests/month at 1,500 in + 500 out tokens pays around $30/month.

How much does GPT-5.5 API cost per 1,000 requests?

At June 2026 pay-as-you-go pricing, GPT-5.5 costs $5.00/1M input tokens and $30/1M output tokens. A typical request with 1,500 input + 500 output tokens costs about $0.0225. For 1,000 such requests, you'd pay approximately $22.50 USD. Use GPT-5.4 nano ($0.20/$1.25) to reduce that cost by ~97%.

What is the cheapest LLM API for high-volume applications?

For high-volume workloads in 2026, GPT-5.4 nano ($0.20/1M input) and Gemini 3.1 Flash-Lite ($0.25/1M input) are the most cost-effective capable options. Claude Haiku 4.5 ($1.00/$5.00) is competitive when output quality matters more.

How do I reduce my LLM API costs in production?

Key strategies: use prompt caching (saves 75–90% on repeated context), switch to GPT-5.4 nano or Gemini 3.1 Flash-Lite for classification tasks, enable batch processing for async jobs, and compress system prompts.