Here's the same token usage priced at different rates: a real long-running coding task, medium codebase, 447 turns.
Input 1,026,957
Output 164,667
Cache read 36,554,368
GPT-6-astra Type Rate Cost Share
Input 10.000 10.270 19%
Output 50.000 8.233 15%
Cache 1.000 36.554 66%
Total 55.057 100%
DeepSeek v4.1 Flash, $0.003 cache hit Type Rate Cost Share
Input 0.300 0.308 50%
Output 1.200 0.198 32%
Cache 0.003 0.110 18%
Total 0.615 100%
DeepSeek v4.1 Flash, $0.006 cache hit Type Rate Cost Share
Input 0.300 0.308 42%
Output 1.200 0.198 27%
Cache 0.006 0.219 30%
Total 0.725 100%
Hypothetical: same DeepSeek input/output rates, but cache priced so it accounts for 66% of the bill. Type Rate Cost Share
Input 0.300 0.308 21%
Output 1.200 0.198 13%
Cache 0.027 0.982 66%
Total 1.487 100%
This cache it improvement makes the model x2-x2.5 more efficient on a long horizon tasks in terms of cost.