AllocateDeepseek V3.1 NVFP4 vs Inkling
On provider list prices, Deepseek V3.1 NVFP4 costs $0.60 per million input tokens against $1.87 for Inkling: 3.1x apart. Output is $1.70 against $4.68 (2.8x). On Allocate both bill at list plus the 7% transaction fee.
Deepseek V3.1 NVFP4
InklingSpecifications 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 $1,315 a month on Deepseek V3.1 NVFP4 and $3,882 on Inkling at list: a gap of $2,567, or 3.0x.
Inkling reads 1M tokens per request against 128K for Deepseek V3.1 NVFP4, 7.6x the window. That decides which one can take whole documents without splitting them.
Choose Deepseek V3.1 NVFP4 for
- The lower list price ($0.60 in / $1.70 out per M tokens)
- Fine-tuning under a permissive license (MIT)
Choose Inkling for
- The longer context window (1M vs 128K tokens)
- Fine-tuning under a permissive license (Apache 2.0)
- Published cached-input pricing ($0.37 per M tokens)
Common questions
Which is cheaper, Deepseek V3.1 NVFP4 or Inkling?
Deepseek V3.1 NVFP4, on this workload shape. At list prices it is $0.60/$1.70 per million tokens in and out against $1.87/$4.68 for Inkling. Billed on Allocate: $0.64/$1.82 against $2.00/$5.01, list plus 7%.
Which has the bigger context window?
Inkling: 1,000,000 tokens (1M) against 131,072 (128K) for Deepseek V3.1 NVFP4.
Can I fine-tune Deepseek V3.1 NVFP4 or Inkling?
Both publish open weights (Deepseek V3.1 NVFP4: MIT; Inkling: 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.