Side-by-side comparison
GPT-5 Nano vs Llama 4 Scout
Meta
Llama 4 Scout
👁 Vision
🔧 Tools
{} JSON
Input / 1M
$0.0800
Output / 1M
$0.3000
| GPT-5 Nano | Llama 4 Scout | |
|---|---|---|
| Provider | OpenAI | Meta |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 400,000 | 327,680 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | vision, tools, json_mode | vision, tools, json_mode |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary → | 0.0500 | 0.0800 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.4000 | 0.3000 |
Frequently asked questions
Which is cheaper, GPT-5 Nano or Llama 4 Scout?
Llama 4 Scout is cheaper than GPT-5 Nano on a 50/50 input/output blend by about $0.035 per 1M tokens. Exact savings depend on your input-vs-output ratio — use the cost calculator on this page for a workload-specific estimate.
Which has a larger context window, GPT-5 Nano or Llama 4 Scout?
GPT-5 Nano has the larger context window at 400k tokens versus 328k tokens for Llama 4 Scout. That means GPT-5 Nano can ingest about 1.2x as much text per request.
What is the difference between GPT-5 Nano and Llama 4 Scout?
GPT-5 Nano comes from OpenAI; Llama 4 Scout comes from Meta. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.