AllocateDeepseek V3.1 NVFP4 vs GPT-5.5
On provider list prices, Deepseek V3.1 NVFP4 costs $0.60 per million input tokens against $5 for GPT-5.5: 8.3x apart. Output is $1.70 against $30 (17.6x). On Allocate both bill at list plus the 7% transaction fee.
Deepseek V3.1 NVFP4
GPT-5.5Specifications 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 $1,315 a month on Deepseek V3.1 NVFP4 and $16,500 on GPT-5.5 at list: a gap of $15,185, or 12.5x.
GPT-5.5 reads 400K tokens per request against 128K for Deepseek V3.1 NVFP4, 3.1x 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)
- Open weights you can fine-tune and own
- Fine-tuning under a permissive license (MIT)
Common questions
Which is cheaper, Deepseek V3.1 NVFP4 or GPT-5.5?
Deepseek V3.1 NVFP4, on this workload shape. At list prices it is $0.60/$1.70 per million tokens in and out against $5/$30 for GPT-5.5. Billed on Allocate: $0.64/$1.82 against $5.35/$32.10, list plus 7%.
Which has the bigger context window?
GPT-5.5: 400,000 tokens (400K) against 131,072 (128K) for Deepseek V3.1 NVFP4.
Can I fine-tune Deepseek V3.1 NVFP4 or GPT-5.5?
Deepseek V3.1 NVFP4 publishes open weights (MIT) and can be fine-tuned on your own data. GPT-5.5 is a closed model served over API; its weights are not available.
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.