Model comparison
GPT-5.5 Pro vs Llama 4 Scout
Compare GPT-5.5 Pro vs Llama 4 Scout API pricing: input/output token costs, cache pricing, context windows, workload estimates, and routing fit.
GPT-5.5 Pro
openai · gpt-5.5-pro
- Input
- $30
- Output
- $180
- Context
- 1.1M
Llama 4 Scout
deepinfra · deepinfra/meta-llama/Llama-4-Scout-17B-16E-Instruct
- Input
- $0.08
- Output
- $0.3
- Context
- 327.7K
Quick take
Llama 4 Scout has the lower input price at $0.08 per 1M input tokens. Llama 4 Scout is cheaper for the example blended workload below. GPT-5.5 Pro has the larger context window at 1.1M tokens.
Choose GPT-5.5 Pro if...
- GPT-5.5 Pro is safer for long documents, repository analysis, and RAG prompts because it has the larger context window.
- GPT-5.5 Pro is stronger when the same large prompt or document is reused because it supports prompt caching.
- GPT-5.5 Pro is required if images, screenshots, or visual documents are part of the workflow.
Choose Llama 4 Scout if...
- Llama 4 Scout is the better default for cost-sensitive traffic and repeated high-volume calls.
- Llama 4 Scout gives more room for long generated answers, reports, or code output.
Example workload cost
Estimates use input tokens plus 20% output tokens. They exclude provider discounts, cache hits, and tool/search surcharges.
| Workload | GPT-5.5 Pro | Llama 4 Scout | Cheaper |
|---|---|---|---|
| 1M input + 200K output | $66.00 | $0.14 | Llama 4 Scout |
| 10M input + 2M output | $660.00 | $1.40 | Llama 4 Scout |
| 100M input + 20M output | $6,600.00 | $14.00 | Llama 4 Scout |
Context, output, and capability fit
GPT-5.5 Pro provides the larger context window. Check max output separately when the task needs long reports, code generation, or full-document rewrites.
- GPT-5.5 Pro max output
- 128K
- Llama 4 Scout max output
- 327.7K
- GPT-5.5 Pro features
- prompt caching, function calling, vision
- Llama 4 Scout features
- function calling
Risk notes for GPT-5.5 Pro
- High output price: cap max tokens for verbose generation workloads.
Risk notes for Llama 4 Scout
- No prompt caching in this snapshot: repeated long-context calls may be more expensive.
Routing tags
frontierpremiumreasoningcodingagentslong-contextmultimodalcache-friendlyragbudgethigh-volumeopen-weightlocal-open