AllocateGemini 3.1 Pro vs Kimi K2.7 Code
On provider list prices, Kimi K2.7 Code costs $0.95 per million input tokens against $2 for Gemini 3.1 Pro: 2.1x apart. Output is $4 against $12 (3.0x). On Allocate both bill at list plus the 7% transaction fee.
Gemini 3.1 Pro
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 $6,600 on Gemini 3.1 Pro at list: a gap of $4,060, or 2.6x.
Gemini 3.1 Pro reads 1M tokens per request against 256K for Kimi K2.7 Code, 3.8x the window. That decides which one can take whole documents without splitting them.
Choose Gemini 3.1 Pro for
- Judgment-heavy workflows
- Long-context analysis
- Escalation tier above Flash
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
- Published cached-input pricing ($0.19 per M tokens)
Common questions
Which is cheaper, Gemini 3.1 Pro 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 $2/$12 for Gemini 3.1 Pro. Billed on Allocate: $1.02/$4.28 against $2.14/$12.84, list plus 7%.
Which has the bigger context window?
Gemini 3.1 Pro: 1,000,000 tokens (1M) against 262,144 (256K) for Kimi K2.7 Code.
Can I fine-tune Gemini 3.1 Pro or Kimi K2.7 Code?
Kimi K2.7 Code publishes open weights (Not listed) and can be fine-tuned on your own data. Gemini 3.1 Pro 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.