AllocateDeepSeek R1 0528 NVFP4 vs GPT-5.5
On provider list prices, DeepSeek R1 0528 NVFP4 costs $3 per million input tokens against $5 for GPT-5.5: 1.7x apart. Output is $7 against $30 (4.3x). On Allocate both bill at list plus the 7% transaction fee.
DeepSeek R1 0528 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 $6,050 a month on DeepSeek R1 0528 NVFP4 and $16,500 on GPT-5.5 at list: a gap of $10,450, or 2.7x.
GPT-5.5 reads 400K tokens per request against 160K for DeepSeek R1 0528 NVFP4, 2.4x the window. That decides which one can take whole documents without splitting them.
Choose DeepSeek R1 0528 NVFP4 for
- The lower list price ($3 in / $7 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 R1 0528 NVFP4 or GPT-5.5?
DeepSeek R1 0528 NVFP4, on this workload shape. At list prices it is $3/$7 per million tokens in and out against $5/$30 for GPT-5.5. Billed on Allocate: $3.21/$7.49 against $5.35/$32.10, list plus 7%.
Which has the bigger context window?
GPT-5.5: 400,000 tokens (400K) against 163,840 (160K) for DeepSeek R1 0528 NVFP4.
Can I fine-tune DeepSeek R1 0528 NVFP4 or GPT-5.5?
DeepSeek R1 0528 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.