Comparisons

GPT-5.5 vs Inkling FP4

On provider list prices, Inkling FP4 costs $1 per million input tokens against $5 for GPT-5.5: 5.0x apart. Output is $4.05 against $30 (7.4x).

GPT-5.5 Inkling FP4
LabOpenAIThinking Machines
AccessAPI onlyOpen weights
Context window400K tokens512K tokens
List price, input$5 / M tokens$1 / M tokens
List price, output$30 / M tokens$4.05 / M tokens
Cached input$0.5 / M tokens$0.17 / M tokens
LicenseProprietary APIApache 2.0
Fine-tunableNoYes

Specifications 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 $2,618 a month on Inkling FP4 and $16,500 on GPT-5.5 at list: a gap of $13,883, or 6.3x.

Inkling FP4 reads 512K tokens per request against 400K for GPT-5.5, 1.3x the window. That decides which one can take whole documents without splitting them.

Inkling FP4$1$4.05
GPT-5.5$5$30
InputOutput

Choose GPT-5.5 for

  • Complex tool-using agents
  • Code generation
  • General assistants
GPT-5.5 details

Choose Inkling FP4 for

  • The lower list price ($1 in / $4.05 out per M tokens)
  • The longer context window (512K vs 400K tokens)
  • Open weights you can fine-tune and own
Inkling FP4 details

Common questions

Which is cheaper, GPT-5.5 or Inkling FP4?

Inkling FP4, on this workload shape. At list prices it is $1/$4.05 per million tokens in and out against $5/$30 for GPT-5.5. Billed on Allocate: $1.07/$4.33 against $5.35/$32.10.

Which has the bigger context window?

Inkling FP4: 524,288 tokens (512K) against 400,000 (400K) for GPT-5.5.

Can I fine-tune GPT-5.5 or Inkling FP4?

Inkling FP4 publishes open weights (Apache 2.0) 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.