Most LLM price pages lead with input and output cost per million tokens. That number is easy to compare and easy to misread. Cache reads change the bill by a factor of 20 to 50, and the discount is not uniform across vendors, so two models with the same input price can end up far apart once prompts get reused.
We keep a price table of 55 models across OpenAI, Anthropic, Google, DeepSeek, xAI and others, checked on 2026-11-11 against each vendor's pricing page. This post pulls out one column that rarely gets compared: what a cached input token costs relative to a fresh one.
The spread
Fifty of the 55 tracked models publish a cache-read price. The ratio to standard input ranges from 2% to 5%.
| Model | Input $/1M | Cached $/1M | Cached share of input |
|---|---|---|---|
| DeepSeek Flash (V4.1) | 0.30 | 0.006 | 2.0% |
| Claude Fable 5.2 | 8.00 | 0.20 | 2.5% |
| Claude Fable 5.1 | 10.00 | 0.25 | 2.5% |
| DeepSeek V4 Pro | 1.32 | 0.044 | 3.3% |
| GPT-6.1 Terra | 1.00 | 0.05 | 5.0% |
| GPT-6.1 Sol | 2.00 | 0.10 | 5.0% |
| Claude Sonnet 5.5 | 2.00 | 0.10 | 5.0% |
| Gemini 4 Carbon | 2.00 | 0.10 | 5.0% |
| Claude Opus 5.5 | 4.00 | 0.20 | 5.0% |
The 2% tier is not the same product as the 5% tier. A 2% cache read means a repeated 100K-token prompt costs 2% of what the first pass cost; at 5% it costs 5%. Over a long agent run that difference is the difference between a workflow that pays for itself and one that does not.
Five models publish no cache price
Mistral Small 4, Codestral 25.08, and the Ministral 3 family (14B, 8B, 3B) list no cache-read rate. That does not mean they are expensive. It means you cannot model a cached workload from the public price page alone, and any comparison that assumes one is guessing.
What this changes in practice
- Compare cache ratios before you compare headline prices. A model at $1 input with a 5% cache read can cost more than a $2 model at 2% once the same context is reused a few times.
- Watch the long-context surcharge. GPT-6 Astra is $10/$50 per million up to 272K input and $20/$75 beyond it, which moves more than the cache discount saves.
- Re-check monthly. This table moved on every check we ran between 2026-11-04 and 2026-11-11.
The full table, with per-model sources and checked dates, is at AI API Cost Calc. If you spot a price that has drifted, the site links every vendor page it was taken from.
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