AllocateDeepseek V3.1 NVFP4 vs Inkling FP4
On provider list prices, Deepseek V3.1 NVFP4 costs $0.60 per million input tokens against $1 for Inkling FP4: 1.7x apart. Output is $1.70 against $4.05 (2.4x).
Deepseek V3.1 NVFP4
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 $1,315 a month on Deepseek V3.1 NVFP4 and $2,618 on Inkling FP4 at list: a gap of $1,303, or 2.0x.
Inkling FP4 reads 512K tokens per request against 128K for Deepseek V3.1 NVFP4, 4.0x 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 FP4 for
- The longer context window (512K vs 128K tokens)
- Fine-tuning under a permissive license (Apache 2.0)
- Published cached-input pricing ($0.17 per M tokens)
Common questions
Which is cheaper, Deepseek V3.1 NVFP4 or Inkling FP4?
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/$4.05 for Inkling FP4. Billed on Allocate: $0.64/$1.82 against $1.07/$4.33.
Which has the bigger context window?
Inkling FP4: 524,288 tokens (512K) against 131,072 (128K) for Deepseek V3.1 NVFP4.
Can I fine-tune Deepseek V3.1 NVFP4 or Inkling FP4?
Both publish open weights (Deepseek V3.1 NVFP4: MIT; 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.