Side-by-side comparison
Llama 4 Scout vs Qwen3.5-Flash
Meta
Llama 4 Scout
👁 Vision
🔧 Tools
{} JSON
Input / 1M
$0.0800
Output / 1M
$0.3000
Qwen
Qwen3.5-Flash
👁 Vision
🔧 Tools
{} JSON
Input / 1M
$0.0650
Output / 1M
$0.2600
| Llama 4 Scout | Qwen3.5-Flash | |
|---|---|---|
| Provider | Meta | Qwen |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 327,680 | 1,000,000 |
| 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 → | 0.0800 | 0.0650 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.3000 | 0.2600 |
Frequently asked questions
Which is cheaper, Llama 4 Scout or Qwen3.5-Flash?
Qwen3.5-Flash is cheaper than Llama 4 Scout on a 50/50 input/output blend by about $0.0275 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, Llama 4 Scout or Qwen3.5-Flash?
Qwen3.5-Flash has the larger context window at 1M tokens versus 328k tokens for Llama 4 Scout. That means Qwen3.5-Flash can ingest about 3.1x as much text per request.
What is the difference between Llama 4 Scout and Qwen3.5-Flash?
Llama 4 Scout comes from Meta; Qwen3.5-Flash comes from Qwen. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.