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We observed cost increases between 49-92%. The price increase is mitigated by the model generating 19-34% fewer completion tokens for longer prompts.
We used the same approach as our Opus 4.7 analysis. We identified users whose top model by request count was GPT-5.4 prior to the 5.5 launch, who then switched to GPT-5.5 as their top model. This “switcher cohort” gives us a controlled before-and-after comparison of the same user base across model versions.
Since GPT-5.4 and 5.5 use the same tokenizer family, we don’t need to control for tokenizer differences. The comparison is direct: same users, same workflows, different model version.
Using OpenRouter’s consistent token counts, we measured how completion lengths changed between models:
| Prompt Size | Median Completion (5.4) | Median Completion (5.5) | Change |
|---|---|---|---|
| < 2K tokens | 121 | 129 | +7% |
| 2K – 10K | 140 | 213 | +52% |
| 10K – 25K | 211 | 143 | -32% |
| 25K – 50K | 185 | 150 | -19% |
| 50K – 128K | 188 | 136 | -28% |
| 128K+ | 215 | 143 | -34% |
For prompts above 10K tokens, GPT-5.5 produces 19-34% fewer tokens. For shorter prompts, the pattern reverses: under 2K tokens completions are roughly the same length, and in the 2K-10K range they are 52% longer.
Using billed costs from requests in the switcher cohort, we calculated the average cost per million OpenRouter tokens. This normalizes for prompt length, allowing a direct comparison of cost efficiency.
| Prompt Size | Avg $/M OR Tokens (5.4) | Avg $/M OR Tokens (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% |
Our analysis shows that GPT-5.5 actual costs increased 49% to 92%. Longer prompts, over 10k tokens, saw costs offset by shorter completions. Shorter prompts, under 10k, experience a higher cost increase where completions did not get shorter.
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