Comparisons

GPT-5.5 vs Llama 4 Scout

On provider list prices, Llama 4 Scout costs $0.18 per million input tokens against $5 for GPT-5.5: 27.8x apart. Output is $0.59 against $30 (50.8x). On Allocate both bill at list plus the 7% transaction fee.

GPT-5.5 Llama 4 Scout
LabOpenAIMeta
AccessAPI onlyOpen weights
Context window400K tokens1M tokens
List price, input$5 / M tokens$0.18 / M tokens
List price, output$30 / M tokens$0.59 / M tokens
Cached input$0.5 / M tokensn/a
LicenseProprietary APILlama community
Fine-tunableNoYes

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 $422.50 a month on Llama 4 Scout and $16,500 on GPT-5.5 at list: a gap of $16,078, or 39.1x.

Llama 4 Scout reads 1M tokens per request against 400K for GPT-5.5, 2.6x the window. That decides which one can take whole documents without splitting them.

Llama 4 Scout$0.18$0.59
GPT-5.5$5$30
InputOutput

Choose GPT-5.5 for

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

Choose Llama 4 Scout for

  • Whole-document reasoning
  • High-volume extraction
  • Fine-tuning under the Llama 4 license
Llama 4 Scout details

Common questions

Which is cheaper, GPT-5.5 or Llama 4 Scout?

Llama 4 Scout, on this workload shape. At list prices it is $0.18/$0.59 per million tokens in and out against $5/$30 for GPT-5.5. Billed on Allocate: $0.19/$0.63 against $5.35/$32.10, list plus 7%.

Which has the bigger context window?

Llama 4 Scout: 1,048,576 tokens (1M) against 400,000 (400K) for GPT-5.5.

Can I fine-tune GPT-5.5 or Llama 4 Scout?

Llama 4 Scout publishes open weights (Llama community) 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.