Comparisons

Kimi K2.7 Code vs Qwen 3.5

On provider list prices, Qwen 3.5 costs $0.60 per million input tokens against $0.95 for Kimi K2.7 Code: 1.6x apart. Output is $3.60 against $4 (1.1x). On Allocate both bill at list plus the 7% transaction fee.

Kimi K2.7 Code Qwen 3.5
LabMoonshot AIQwen
AccessOpen weightsOpen weights
Context window256K tokens256K tokens
List price, input$0.95 / M tokens$0.6 / M tokens
List price, output$4 / M tokens$3.6 / M tokens
Cached input$0.19 / M tokens$0.35 / M tokens
LicenseNot listedApache 2.0
Fine-tunableYesYes

Specifications 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 $1,980 a month on Qwen 3.5 and $2,540 on Kimi K2.7 Code at list: a gap of $560, or 1.3x.

Qwen 3.5$0.60$3.60
Kimi K2.7 Code$0.95$4
InputOutput

Choose Kimi K2.7 Code for

  • Training toward a model you own
Kimi K2.7 Code details

Choose Qwen 3.5 for

  • Multilingual support agents
  • Translation-adjacent workflows
  • Fine-tuning under Apache 2.0
Qwen 3.5 details

Common questions

Which is cheaper, Kimi K2.7 Code or Qwen 3.5?

Qwen 3.5, on this workload shape. At list prices it is $0.60/$3.60 per million tokens in and out against $0.95/$4 for Kimi K2.7 Code. Billed on Allocate: $0.64/$3.85 against $1.02/$4.28, list plus 7%.

Which has the bigger context window?

They match: both read 262,144 tokens (256K) per request.

Can I fine-tune Kimi K2.7 Code or Qwen 3.5?

Both publish open weights (Kimi K2.7 Code: Not listed; Qwen 3.5: Apache 2.0), so both can be fine-tuned. On Allocate the trained weights stay inside your boundary and belong to you.

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.