AllocateGPT-5.5 vs Kimi K2.7 Code
On provider list prices, Kimi K2.7 Code costs $0.95 per million input tokens against $5 for GPT-5.5: 5.3x apart. Output is $4 against $30 (7.5x). On Allocate both bill at list plus the 7% transaction fee.
GPT-5.5
Kimi K2.7 CodeSpecifications and provider list prices from the Allocate catalog, checked 2026-07-08. Billed price is list plus the 7% transaction fee.
What the numbers say
Take 1,000,000 requests a month at 1,200 input and 350 output tokens each. That workload costs $2,540 a month on Kimi K2.7 Code and $16,500 on GPT-5.5 at list: a gap of $13,960, or 6.5x.
GPT-5.5 reads 400K tokens per request against 256K for Kimi K2.7 Code, 1.5x the window. That decides which one can take whole documents without splitting them.
Choose Kimi K2.7 Code for
- The lower list price ($0.95 in / $4 out per M tokens)
- Open weights you can fine-tune and own
Common questions
Which is cheaper, GPT-5.5 or Kimi K2.7 Code?
Kimi K2.7 Code, on this workload shape. At list prices it is $0.95/$4 per million tokens in and out against $5/$30 for GPT-5.5. Billed on Allocate: $1.02/$4.28 against $5.35/$32.10, list plus 7%.
Which has the bigger context window?
GPT-5.5: 400,000 tokens (400K) against 262,144 (256K) for Kimi K2.7 Code.
Can I fine-tune GPT-5.5 or Kimi K2.7 Code?
Kimi K2.7 Code publishes open weights (Not listed) and can be fine-tuned on your own data. GPT-5.5 is a closed model served over API; its weights are not available.
Related comparisons
Run the numbers on your workload
Or don’t choose. On Allocate a route name is the contract: point yours at one model today, swap to the other tomorrow, and compare them on your live traffic with per-token metering.