AllocateOpenAI GPT-OSS 20B vs Inkling FP4
On provider list prices, OpenAI GPT-OSS 20B costs $0.05 per million input tokens against $1 for Inkling FP4: 20.0x apart. Output is $0.20 against $4.05 (20.2x).
OpenAI GPT-OSS 20B
Inkling FP4Specifications and provider list prices from the Allocate catalog, checked 2026-07-21.
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 $2,618 on Inkling FP4 at list: a gap of $2,488, or 20.1x.
Inkling FP4 reads 512K tokens per request against 128K for OpenAI GPT-OSS 20B, 4.0x the window. That decides which one can take whole documents without splitting them.
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)
Choose Inkling FP4 for
- The longer context window (512K vs 128K tokens)
- Fine-tuning under a permissive license (Apache 2.0)
- Published cached-input pricing ($0.17 per M tokens)
Common questions
Which is cheaper, OpenAI GPT-OSS 20B or Inkling FP4?
OpenAI GPT-OSS 20B, on this workload shape. At list prices it is $0.05/$0.20 per million tokens in and out against $1/$4.05 for Inkling FP4. Billed on Allocate: $0.053/$0.21 against $1.07/$4.33.
Which has the bigger context window?
Inkling FP4: 524,288 tokens (512K) against 131,072 (128K) for OpenAI GPT-OSS 20B.
Can I fine-tune OpenAI GPT-OSS 20B or Inkling FP4?
Both publish open weights (OpenAI GPT-OSS 20B: Apache 2.0; Inkling FP4: 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.