Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input...
Model details →Meta: Llama 4 Scout vs OpenRouter: Fusion
Meta: Llama 4 Scout wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
Fusion turns your prompt into a small multi-model deliberation. A panel of expert models (see below) analyzes your prompt in parallel with web search and web fetch enabled, then a...
Model details →Side-by-side comparison
| Capability | Meta: Llama 4 Scout | OpenRouter: Fusion | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 1.3M | 1M | 🏆 Meta: Llama 4 Scout |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $0.10 | $-1000000.00 | 🏆 OpenRouter: Fusion |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $0.30 | $-1000000.00 | 🏆 OpenRouter: Fusion |
| Tool / function calling First-class support for emitting structured tool calls. | Yes | — | 🏆 Meta: Llama 4 Scout |
| Vision input Accepts image inputs alongside text. | Yes | — | 🏆 Meta: Llama 4 Scout |
| Reasoning mode Internal chain-of-thought / extended-thinking support. | — | — | Tie |
Frequently asked questions
Is Meta: Llama 4 Scout better than OpenRouter: Fusion?
Meta: Llama 4 Scout wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between Meta: Llama 4 Scout and OpenRouter: Fusion?
Input: $0.10 vs $-1000000.00 per 1M tokens. Output: $0.30 vs $-1000000.00 per 1M tokens.
What context windows do Meta: Llama 4 Scout and OpenRouter: Fusion support?
Meta: Llama 4 Scout supports up to 1.3M tokens. OpenRouter: Fusion supports up to 1M tokens.
Do both Meta: Llama 4 Scout and OpenRouter: Fusion support tool calling?
Meta: Llama 4 Scout: yes. OpenRouter: Fusion: not advertised.
Compare Meta: Llama 4 Scout with other models
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