Llama 4 Scout Pricing
FastMeta · 10M tokens context
Llama 4 Scout from Meta costs $0.100 per 1 million input tokens and $0.300 per 1 million output tokens as of June 2026 (live OpenRouter data). The model supports a 10,000,000-token context window (approximately 7,500,000 words) with a 16K-token maximum output. A typical 1,000-token request costs $0.0001 in input charges; a 10,000-token request costs $0.0010.
| Input price | $0.100 / 1M tokens |
|---|---|
| Output price | $0.300 / 1M tokens |
| Output / input ratio | 3.0× |
| Context window | 10,000,000 tokens (~7,500,000 words) |
| Maximum output | 16,384 tokens |
| Cost per 1K tokens (input) | $0.0001 |
| Tier | Fast |
| Last verified |
Llama 4 Scout is Meta's latest MoE model with an industry-leading 10M token context window at an affordable price. Remarkable context-to-cost ratio — suitable for entire-codebase and very long document tasks.
Input Price
$0.100
per 1 million tokens
Output Price
$0.300
per 1 million tokens
Context Window
10M tokens
max 16K output
Cost Examples
| Request Type | Tokens | Input Cost | Output Cost |
|---|---|---|---|
| 1,000 word article | 1,333 | $0.000133 | $0.00012 |
| 10-page document (2,500 words) | 3,333 | $0.000333 | $0.0003 |
| 1,000 lines of code | 5,000 | $0.0005 | $0.00045 |
| 100K token document | 100,000 | $0.01 | $0.009 |
Output cost estimated at 30% of input token count. Use the calculator for exact figures.
Strengths
- ✓10M token context window — largest available
- ✓Very cheap at $0.17/1M symmetric
- ✓MoE architecture for efficient inference
- ✓Open weights
Limitations
- –Very long contexts require specialist infrastructure
- –MoE quality varies by host
Best Use Cases
Calculate Llama 4 Scout Costs
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Open Calculator →Llama 4 Scout — FAQ
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