Meta: Llama 4 Scout
Meta: Llama 4 Scout is the budget pick for big-context workloads that would feel wasteful on pricier models. It handles vision, tools, and structured output, while staying firmly in the cheap tier at $0.08 input and $0.30 output per 1M tokens. The surprising part is how little long jobs cost here: a long PDF plus follow-up questions is about $0.01, and even a 50-step agent workflow is about $0.01.
Best for
- •Reading long PDFs, docs, or logs when you want context headroom without watching token costs.
- •Low-cost agent workflows that need tool use and structured outputs more than premium writing quality.
- •High-volume coding or automation tasks where 1,000 completions for about $0.14 is hard to ignore.
Not ideal for
- •Polished final-copy writing where you care more about tone, judgment, or nuance than raw affordability.
- •Cases where you want bundled app access, since no subscriptions including this model were found in StackTrim AI.
What it costs in real life
Computed from OpenRouter API pricing ($0.08 input / $0.30 output per 1M tokens)
Frequently Asked Questions
Is Meta: Llama 4 Scout worth it for long PDFs and research notes?
Yes, if your main goal is to process a lot of text cheaply. Its 320K context and low token pricing make it a practical choice for document-heavy work, especially when a long PDF plus questions costs about $0.01.
How expensive is Meta: Llama 4 Scout API use compared with other models?
It sits clearly in the cheap tier at $0.08 per 1M input tokens and $0.30 per 1M output tokens. That pricing makes it easy to justify for repeated workflows, coding batches, and agent-style tasks where token volume adds up fast.
Can Meta: Llama 4 Scout handle coding, tools, and images in one workflow?
Yes, that is one of the more practical reasons to use it. It supports vision, tools, and structured output, so it fits workflows where you need one low-cost model to inspect inputs, call tools, and return machine-readable results.
Capabilities
Cheapest access path
The cheapest way to use it is direct API usage at $0.08 per 1M input tokens and $0.30 per 1M output tokens. In practice, that keeps common jobs tiny in cost: 100 short chats cost about $0.01, and 1 long PDF with questions also lands around $0.01.