Free LLM & API Cost Calculators 2026 | APICalculators
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2026 pricing · 12 calculators · runs 100% in your browser<br>Free LLM & API Cost Calculator — Know Your Infra Bill Before It Arrives.
Real-time cost calculators for LLM tokens, vector databases, cloud VPS, serverless, auth providers, AI coding tools and payment fees. 12 free tools, zero signup.
12+ Providers
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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.
Model
Input tokens / request avg
Output tokens / request avg
Requests per period
Billing period
Per day<br>Per month<br>Per year
Estimated cost
$0
— per month
Price (input / output per 1M)—
Cost per request—
Input token cost—
Output token cost—
Total tokens / period—
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.
Full LLM calculator with all models →
More API Cost Calculators
11 free tools — click to open the full interactive calculator with all providers and options.
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🎨<br>Image Generation Cost
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💳<br>Payment Processor Fees
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☁️<br>Cloud VPS Comparison
Hetzner vs DigitalOcean vs Vultr
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🎙️<br>STT / TTS API Cost
Whisper vs ElevenLabs vs Deepgram
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Serverless Cost Calculator
Lambda vs Vercel vs Cloudflare Workers
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🔀<br>API Gateway Pricing
AWS API GW vs Cloudflare vs Kong
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🧲<br>Embedding API Cost
OpenAI vs Cohere vs Voyage AI
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🤖<br>AI Agent Cost
Multi-step pipeline pricing per run
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💻<br>AI Coding Tool Cost
Cursor vs Copilot vs Claude Code
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🔑<br>Auth Provider Cost
Clerk vs Supabase Auth vs Auth0
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Frequently asked questions
Everything about how these calculators work and where the numbers come from.
How accurate are the LLM pricing calculations? +
They use published 2026 public API rates from OpenAI, Anthropic, Google and others, reviewed monthly. They don't include negotiated enterprise discounts, prompt caching, or batch-API savings — so treat them as an upper-bound budgeting estimate.
Is APICalculators free to use? +
Yes. Every calculator is free with no registration, login, or paywall. We sustain the site through display ads and affiliate partnerships.
Do you store or send my data anywhere? +
No. All math runs entirely in your browser with JavaScript. Nothing you type is transmitted to a server or persisted beyond your session.
Why do vector DB and image estimates vary from my real bill? +
Those providers price on complex dimensions (read units, pod-hours, GPU time, plan tiers). We use simplified, transparent models for apples-to-apples comparison — great for choosing a...