AllocateDeepSeek R1 Distill Qwen 14B vs Kimi K2.5
On provider list prices, DeepSeek R1 Distill Qwen 14B costs $1.60 per million input tokens against $0.50 for Kimi K2.5: effectively level. Output is $1.60 against $2.80 (1.7x). On Allocate both bill at list plus the 7% transaction fee.
DeepSeek R1 Distill Qwen 14B
Kimi K2.5Specifications 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 $1,580 a month on Kimi K2.5 and $2,480 on DeepSeek R1 Distill Qwen 14B at list: a gap of $900, or 1.6x.
Kimi K2.5 reads 256K tokens per request against 128K for DeepSeek R1 Distill Qwen 14B, 2.0x the window. That decides which one can take whole documents without splitting them.
Choose DeepSeek R1 Distill Qwen 14B for
- Fine-tuning under a permissive license (MIT)
Choose Kimi K2.5 for
- Whole-document reasoning
- Long-context retrieval
- Open-weight fine-tuning
Common questions
Which is cheaper, DeepSeek R1 Distill Qwen 14B or Kimi K2.5?
Kimi K2.5, on this workload shape. At list prices it is $0.50/$2.80 per million tokens in and out against $1.60/$1.60 for DeepSeek R1 Distill Qwen 14B. Billed on Allocate: $0.54/$3.00 against $1.71/$1.71, list plus 7%.
Which has the bigger context window?
Kimi K2.5: 262,144 tokens (256K) against 131,072 (128K) for DeepSeek R1 Distill Qwen 14B.
Can I fine-tune DeepSeek R1 Distill Qwen 14B or Kimi K2.5?
Both publish open weights (DeepSeek R1 Distill Qwen 14B: MIT; Kimi K2.5: Not listed), 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.