AllocateKimi K2.5 vs Qwen 3.5
On provider list prices, Kimi K2.5 costs $0.50 per million input tokens against $0.60 for Qwen 3.5: 1.2x apart. Output is $2.80 against $3.60 (1.3x).
Kimi K2.5
Qwen 3.5Specifications and provider list prices from the Allocate catalog, checked 2026-07-21.
What the numbers say
Take 1,000,000 requests a month at 1,200 input and 350 output tokens each. That workload costs $1,580 a month on Kimi K2.5 and $1,980 on Qwen 3.5 at list: a gap of $400, or 1.3x.
Choose Kimi K2.5 for
- Whole-document reasoning
- Long-context retrieval
- Open-weight fine-tuning
Choose Qwen 3.5 for
- Multilingual support agents
- Translation-adjacent workflows
- Fine-tuning under Apache 2.0
Common questions
Which is cheaper, Kimi K2.5 or Qwen 3.5?
Kimi K2.5, on this workload shape. At list prices it is $0.50/$2.80 per million tokens in and out against $0.60/$3.60 for Qwen 3.5. Billed on Allocate: $0.54/$3.00 against $0.64/$3.85.
Which has the bigger context window?
They match: both read 262,144 tokens (256K) per request.
Can I fine-tune Kimi K2.5 or Qwen 3.5?
Both publish open weights (Kimi K2.5: 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.