LLM‑Preise

Über diese Liste

Almost every commercial LLM provider charges separately for input tokens (the prompt you send) and output tokens (the response you get back). Output tokens typically cost 3–5× more than input tokens because generation is autoregressive — each token depends on the previous one and cannot be batched as efficiently.

The table below normalises all prices to USD per 1 million tokens. This is the industry-standard unit; per-1K or per-token rates are easy to misread by 1000×. The "Total" column sums input + output for a quick apples-to-apples comparison, but your real cost depends heavily on your input/output ratio.

What the table does NOT show

• Prompt caching discounts — Anthropic and OpenAI offer cache_read rates 5–10× cheaper than standard input. If you reuse a long system prompt, caching dominates total cost.
• Tiered pricing above 200K tokens — Google and Anthropic charge a premium for very long inputs. Each model detail page shows the >200K tier when applicable.
• Reasoning tokens — thinking models (o-series, Claude Extended Thinking, DeepSeek R1) bill internal reasoning at output rates, often 2–3× the visible answer length.
• Volume discounts and prepaid credits — most providers offer 10–30% off at scale. These are not reflected here.
• Audio / image surcharges — multimodal inputs have separate per-image or per-second rates.

How to use this page

1. Find the cheapest model that meets your context window and capability requirements (tool calling, structured output, vision).
2. Open its detail page to check cache pricing, output limits and provider availability.
3. Use the pricing calculator to estimate monthly cost for your actual token volume.
4. Compare 2–3 finalists side-by-side on a comparison page.

Prices are refreshed daily. Models showing "Unknown" do not publish a public per-token rate — this usually means enterprise-only or invite-gated access. We deliberately do not show them as $0 to avoid misleading rankings.