AllocateDeepseek V3.1 NVFP4 vs OpenAI GPT-OSS 20B
On provider list prices, OpenAI GPT-OSS 20B costs $0.05 per million input tokens against $0.60 for Deepseek V3.1 NVFP4: 12.0x apart. Output is $0.20 against $1.70 (8.5x). On Allocate both bill at list plus the 7% transaction fee.
Deepseek V3.1 NVFP4
OpenAI GPT-OSS 20BSpecifications 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 $130 a month on OpenAI GPT-OSS 20B and $1,315 on Deepseek V3.1 NVFP4 at list: a gap of $1,185, or 10.1x.
Choose Deepseek V3.1 NVFP4 for
- Fine-tuning under a permissive license (MIT)
Choose OpenAI GPT-OSS 20B for
- The lower list price ($0.05 in / $0.20 out per M tokens)
- Fine-tuning under a permissive license (Apache 2.0)
Common questions
Which is cheaper, Deepseek V3.1 NVFP4 or OpenAI GPT-OSS 20B?
OpenAI GPT-OSS 20B, on this workload shape. At list prices it is $0.05/$0.20 per million tokens in and out against $0.60/$1.70 for Deepseek V3.1 NVFP4. Billed on Allocate: $0.053/$0.21 against $0.64/$1.82, list plus 7%.
Which has the bigger context window?
They match: both read 131,072 tokens (128K) per request.
Can I fine-tune Deepseek V3.1 NVFP4 or OpenAI GPT-OSS 20B?
Both publish open weights (Deepseek V3.1 NVFP4: MIT; OpenAI GPT-OSS 20B: 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.