AllocateDeepSeek R1 0528 NVFP4 vs OpenAI GPT-OSS 120B
On provider list prices, OpenAI GPT-OSS 120B costs $0.15 per million input tokens against $3 for DeepSeek R1 0528 NVFP4: 20.0x apart. Output is $0.60 against $7 (11.7x). On Allocate both bill at list plus the 7% transaction fee.
DeepSeek R1 0528 NVFP4
OpenAI GPT-OSS 120BSpecifications 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 $390 a month on OpenAI GPT-OSS 120B and $6,050 on DeepSeek R1 0528 NVFP4 at list: a gap of $5,660, or 15.5x.
DeepSeek R1 0528 NVFP4 reads 160K tokens per request against 128K for OpenAI GPT-OSS 120B, 1.3x the window. That decides which one can take whole documents without splitting them.
Choose DeepSeek R1 0528 NVFP4 for
- The longer context window (160K vs 128K tokens)
- Fine-tuning under a permissive license (MIT)
Choose OpenAI GPT-OSS 120B for
- The lower list price ($0.15 in / $0.60 out per M tokens)
Common questions
Which is cheaper, DeepSeek R1 0528 NVFP4 or OpenAI GPT-OSS 120B?
OpenAI GPT-OSS 120B, on this workload shape. At list prices it is $0.15/$0.60 per million tokens in and out against $3/$7 for DeepSeek R1 0528 NVFP4. Billed on Allocate: $0.16/$0.64 against $3.21/$7.49, list plus 7%.
Which has the bigger context window?
DeepSeek R1 0528 NVFP4: 163,840 tokens (160K) against 131,072 (128K) for OpenAI GPT-OSS 120B.
Can I fine-tune DeepSeek R1 0528 NVFP4 or OpenAI GPT-OSS 120B?
Both publish open weights (DeepSeek R1 0528 NVFP4: MIT; OpenAI GPT-OSS 120B: Custom license), 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.