Kimi K2.5 vs Llama 4 Scout
On provider list prices, Llama 4 Scout costs $0.18 per million input tokens against $0.50 for Kimi K2.5: 2.8x apart. Output is $0.59 against $2.80 (4.7x). On Allocate both bill at list plus the 7% transaction fee.
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 $422.50 a month on Llama 4 Scout and $1,580 on Kimi K2.5 at list: a gap of $1,158, or 3.7x.
Llama 4 Scout reads 1M tokens per request against 256K for Kimi K2.5, 4.0x the window. That decides which one can take whole documents without splitting them.
Choose Kimi K2.5 for
- Whole-document reasoning
- Long-context retrieval
- Open-weight fine-tuning
Choose Llama 4 Scout for
- Whole-document reasoning
- High-volume extraction
- Fine-tuning under the Llama 4 license
Common questions
Which is cheaper, Kimi K2.5 or Llama 4 Scout?
Llama 4 Scout, on this workload shape. At list prices it is $0.18/$0.59 per million tokens in and out against $0.50/$2.80 for Kimi K2.5. Billed on Allocate: $0.19/$0.63 against $0.54/$3.00, list plus 7%.
Which has the bigger context window?
Llama 4 Scout: 1,048,576 tokens (1M) against 262,144 (256K) for Kimi K2.5.
Can I fine-tune Kimi K2.5 or Llama 4 Scout?
Both publish open weights (Kimi K2.5: Not listed; Llama 4 Scout: Llama community), 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.