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AI API Cost Calculator

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AI API Costs

Estimate your AI spending, compare model pricing, and understand what your real-world workloads actually cost.

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11Pricing guides
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Oct 2026Prices verified

Claude Opus 5.5 API Pricing: Per-Token Costs and Workload Math

How much does the Claude Opus 5.5 API cost per 1M tokens? Claude Opus 5.5 costs $4.00 per 1M input tokens , $0.20 per 1M cached input tokens , and $20.00 per 1M output tokens . Cache reads run at 5% of the input price — half the ratio of most Claude models, and the deepest cut in this release. Last verified: October 2026, against Anthropic's official pricing documentation. The Full Price Table Straight from Anthropic's published rate card (standard tier): Token type Price per 1M tokens Input $4.00 Cached input (reads) $0.20 Cache writes (5-minute) $5.00 Cache writes (1-hour) $8.00 Output $20.00 The cache-read line is the story of this release. On most Claude models a cache hit costs 10% of the input price; on Opus 5.5 it's 5% . Anthropic kept the standard write multipliers — 1.25x input for the default 5-minute cache, 2x for the 1-hour option — so the first call that establishes a new cache prefix costs slightly more than an uncached call, and every reuse after...
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GPT-6.1 Sol API Pricing: Per-Token Costs and Workload Math

How much does the GPT-6.1 Sol API cost per 1M tokens? GPT-6.1 Sol costs $2.00 per 1M input tokens , $0.10 per 1M cached input tokens , and $10.00 per 1M output tokens . The cached-input rate — 5% of the standard input price — is the cheapest OpenAI has published for a model in this class. Last verified: October 2026, against OpenAI's official GPT-6.1 Sol model page. The Full Price Table Straight from OpenAI's published rate card (standard tier, short context): Token type Price per 1M tokens Input $2.00 Cached input $0.10 Cache writes $2.50 Output $10.00 Two details worth knowing. First, cached input is priced at exactly 5% of the uncached input rate, and cache writes cost 1.25x the input rate — so the first call that establishes a new cache prefix costs slightly more than an uncached call, and every reuse after that is nearly free. Second, this is the standard list price with no promo expiry attached — unlike GPT-5.6 Sol (promo "at least through November 21, 2...
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AI API Cost Calculator: Estimate Your Monthly LLM Bill

AI API Cost Calculator Estimate your monthly LLM API spend. Enter your workload below and compare costs across models . Prices verified October 2026 — always re-check the provider's pricing page before budgeting. Tasks per month Fresh input tokens / task Cached input tokens / task Output tokens / task Batch API mode (50% off — for work that can wait hours) Your cost per model Prices per 1M tokens, verified Oct 2026. GPT-5.6 Sol promo: "available at least through Nov 21, 2026" (OpenAI). Argon intro through Nov 30, 2026, then $4/$20 from Dec 1. "Post-promo" Sol uses the pre-promo $5/$30 list price as the only concrete scenario — not a prediction. All cache rates shown are published rate-card figures. This is an estimate, not a quote.
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AI Subscriptions vs API Pricing: Where's the Crossover?

Last updated: October 2026 If you're building with AI, you eventually face a deceptively simple question: should I just pay for the subscription, or pay per token through the API? The answer isn't a preference — it's math. And the math has a crossover point most developers never calculate. The $200/Month Rule of Thumb Here's the heuristic, stated up front as what it is — a rule of thumb, not a law: under ~$200/month of usage , a flat subscription usually wins. Above ~$200/month , metered API pricing — with caching and routing — is typically cheaper and scales linearly. At low volumes, the flat fee is subsidized — you're getting more value than you pay for. At high volumes, you become the heavy user everyone else is averaged against, and the meter starts looking generous by comparison. Why Subscriptions Win at Low Volume 1. The flat fee subsidizes exploration. Bursty, unpredictable usage — a heavy week costs the same as a light one. On the API, every experimen...
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Batch API vs Real-Time: When 50% Off Is Worth the Wait

Last updated: October 2026 Every major LLM provider sells the same model at two prices: full price for answers in seconds, roughly half price for answers in hours. The Batch API is the most underused discount in the industry — same model, same quality, ~50% off, in exchange for patience. Here's when it's worth it and when it isn't. What Batch Mode Actually Is A batch request is exactly what it sounds like: you submit a batch of requests as a file, the provider processes them when it has spare capacity, and you collect the results later — typically within 24 hours. Same weights, same capabilities, same output quality. The discount exists because you're letting the provider schedule your work during off-peak capacity instead of demanding instant compute. On GPT-5.6 Sol, batch processing cuts the promo rates in half — $2.00 input / $10.00 output per 1M tokens instead of $4.00/$20.00. The mechanics are simple: upload a JSONL file of requests, poll for completion, down...
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Prompt Caching: The 90% Discount You're Missing

Last updated: October 2026 There is a 90% discount sitting in your API bill , and most developers are either not using it or using it in a way that doesn't work. Prompt caching — paying a tenth of the input price for tokens the provider has already seen — is the highest-leverage cost optimization available on modern LLM APIs. Here's how it actually works and how to get the savings. How Prompt Caching Actually Works The idea is simple. When you send a request, the provider processes your input tokens through the model — that's the expensive computation you're paying for. But if your next request starts with the exact same tokens — the same system prompt, the same repo context, the same few-shot examples — the provider doesn't need to recompute all of that. It kept the intermediate results cached. So it charges you a fraction of the price for those repeated tokens. The key phrase is stable prefix . Caching works from the start of your prompt forward: the provider...
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Cheapest LLM API in 2026: What to Actually Pick

Last updated: October 2026 "What's the cheapest LLM API?" is the wrong question — or rather, it's a question with a trap in it. The model with the lowest per-token price is rarely the cheapest one on your invoice. Your real bill is decided by three things the headline price doesn't show: cache rates, output ratios, and pricing thresholds. Here's the honest comparison, using only verified current prices. The Verified Price Table These are the models with confirmed pricing as of October 2026. No rumors, no "reportedly" — just published rate cards: Model Input / 1M Cached input / 1M Output / 1M GPT-5.6 Sol (promo) $4.00 $0.40 $20.00 GPT-6.1 Sol $2.00 $0.10 $10.00 Claude Opus 5.5 $4.00 $0.20 $20.00 Claude Sonnet 5.5 $2.00 $0.20 $10.00 Gemini 4 Argon (intro) $2.00 $0.10 $10.00 Gemini 4 Argon (from Dec 1) $4.00 $0.20 $20.00 Muse Wonder $4.00 $0.20 $20.00 Two deadlines matter here. GPT-5.6 Sol's promo is "available at least through N...
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