For longer prompts of more than 10,000 tokens, GPT-5.5 produces responses that are 19% to 34% shorter, which helps reduce the cost impact somewhat. For medium-length prompts between 2,000 and 10,000 tokens, however, responses are around 52% longer. With short prompts below 2,000 tokens, answer length remains roughly unchanged, meaning users face almost a full doubling of costs. The figures are based on OpenRouter’s own usage logs from April 2026.

Input length

Avg. $/M tokens GPT-5.4

Avg. $/M tokens GPT-5.5

Change

< 2K tokens

$4.89

$9.37

+92%

2K–10K

$2.25

$3.81

+69%

10K–25K

$1.42

$2.15

+51%

25K–50K

$1.02

$1.65

+62%

50K–128K

$0.74

$1.10

+49%

128K+

$0.71

$1.31

+85%

A previous analysis by Artificial Analysis had estimated the price increase at around 20%, but that test relied on benchmarks rather than real-world workloads. Anthropic has also moved in a similar direction with Opus 4.7, where higher token usage pushed effective costs up by 30% to 40%. With both companies moving closer to potential IPOs, further price increases may remain a realistic scenario.

The effective cost increase of GPT-5.5 shows that nominal pricing alone no longer gives an accurate picture of model economics. For businesses and developers, real-world token behavior — especially output length across different task types — is becoming just as important as the official price per million tokens.