Which LLM API is the cheapest?

Among current-generation flagship families, GPT-5.6 Luna is the cheapest at 0.20/1.20 per million tokens, following OpenAI's July 30, 2026 price cut. Open-weight and offshore providers undercut it on output, at the cost of smaller context windows and, for most enterprises, a data governance review.

Is there a completely free LLM API?

Sort of. Major providers offer expiring trial credits, Google's AI Studio has a development free tier, and open-weight models are available free with rate limits. Nothing free survives production traffic; free tiers are for evaluation, and the metered spend starts silently when they run out.

Is Claude cheaper than OpenAI?

Tier by tier: Claude Opus 5 beats GPT-5.6 Sol on output ($25 vs $30) at matched $5 input. OpenAI's Luna undercuts every Claude model on sticker price. Claude counters with no long-context surcharge, where OpenAI roughly doubles rates above ~272K tokens, so context-heavy workloads often flip to Anthropic despite the table.

How much does 1 million tokens cost?

Between $0.20 and $30 on input and $0.42 and $180 on output across mainstream models, a spread wide enough that "how much do tokens cost" has no single answer. Multiply your expected mix by the table above, or use the calculator linked in the workload section.

What is the best LLM for the price?

Depends on the task, and benchmarks only get you to a shortlist. The reliable pattern: route high-volume simple work to the $0.20 to $1 tier, production defaults to the $2 tier, and flagships only where your own evaluations show a measurable lift worth 2.5x the cost. Then instrument the spend so the answer stays true as prices move.

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