AllocateKimi K2.5 vs Inkling FP4
On provider list prices, Kimi K2.5 costs $0.50 per million input tokens against $1 for Inkling FP4: 2.0x apart. Output is $2.80 against $4.05 (1.4x).
Kimi K2.5
Inkling FP4Specifications 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 $2,618 on Inkling FP4 at list: a gap of $1,038, or 1.7x.
Inkling FP4 reads 512K tokens per request against 256K for Kimi K2.5, 2.0x 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 Inkling FP4 for
- The longer context window (512K vs 256K tokens)
- Fine-tuning under a permissive license (Apache 2.0)
- Published cached-input pricing ($0.17 per M tokens)
Common questions
Which is cheaper, Kimi K2.5 or Inkling FP4?
Kimi K2.5, on this workload shape. At list prices it is $0.50/$2.80 per million tokens in and out against $1/$4.05 for Inkling FP4. Billed on Allocate: $0.54/$3.00 against $1.07/$4.33.
Which has the bigger context window?
Inkling FP4: 524,288 tokens (512K) against 262,144 (256K) for Kimi K2.5.
Can I fine-tune Kimi K2.5 or Inkling FP4?
Both publish open weights (Kimi K2.5: Not listed; Inkling FP4: 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.