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DeepSeek R1 0528 NVFP4 vs OpenAI GPT-OSS 20B

On provider list prices, OpenAI GPT-OSS 20B costs $0.05 per million input tokens against $3 for DeepSeek R1 0528 NVFP4: 60.0x apart. Output is $0.20 against $7 (35.0x). On Allocate both bill at list plus the 7% transaction fee.

DeepSeek R1 0528 NVFP4 OpenAI GPT-OSS 20B
LabDeepseekOpenAI
AccessOpen weightsOpen weights
Context window160K tokens128K tokens
List price, input$3 / M tokens$0.05 / M tokens
List price, output$7 / M tokens$0.2 / M tokens
Cached inputn/an/a
LicenseMITApache 2.0
Fine-tunableYesYes

Specifications 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 $6,050 on DeepSeek R1 0528 NVFP4 at list: a gap of $5,920, or 46.5x.

DeepSeek R1 0528 NVFP4 reads 160K tokens per request against 128K for OpenAI GPT-OSS 20B, 1.3x the window. That decides which one can take whole documents without splitting them.

OpenAI GPT-OSS 20B$0.05$0.20
DeepSeek R1 0528 NVFP4$3$7
InputOutput

Choose DeepSeek R1 0528 NVFP4 for

  • The longer context window (160K vs 128K tokens)
  • Fine-tuning under a permissive license (MIT)
DeepSeek R1 0528 NVFP4 details

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)
OpenAI GPT-OSS 20B details

Common questions

Which is cheaper, DeepSeek R1 0528 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 $3/$7 for DeepSeek R1 0528 NVFP4. Billed on Allocate: $0.053/$0.21 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 20B.

Can I fine-tune DeepSeek R1 0528 NVFP4 or OpenAI GPT-OSS 20B?

Both publish open weights (DeepSeek R1 0528 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

DeepSeek R1 0528 NVFP4 vs Deepseek V4 ProOpenAI GPT-OSS 20B vs Deepseek V4 ProDeepSeek R1 0528 NVFP4 vs OpenAI GPT-OSS 120BOpenAI GPT-OSS 20B vs OpenAI GPT-OSS 120BDeepSeek R1 0528 NVFP4 vs GPT-5.5OpenAI GPT-OSS 20B vs GPT-5.5

Run the numbers on your workload

LLM price comparisonAgent cost calculatorDeepSeek R1 0528 NVFP4OpenAI GPT-OSS 20B

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.

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