Meta
Llama 4 Scout
Overall 73Open weightopen-weightMeta's Llama 4 Scout (17Bx16E MoE, 109B total params) with an extraordinary 10M token context window.
Capability profile
Radar view of the model's practical strengths. This chart is backed by textual summaries below for crawlability.
Benchmark summary
This entry has source-backed metadata, but benchmark coverage is still sparse, so the page emphasizes published specs and deployment fit.
No benchmark series is attached to this model yet. Source links and product metadata are available below.
Strengths
- • Source-backed listing for open-weight text model buyers
- • Useful when deeper benchmark profiling is still incomplete
Trade-offs
- • Detailed benchmark coverage is still limited for this entry
- • Some pricing or capability fields may remain unpublished
Crawlable benchmark analysis
Llama 4 Scout is positioned as an open-weight text model with published scores that emphasize its practical fit for buyers evaluating the entry.
Published scores highlight reasoning 77/100, coding 68/100, enterprise readiness 60/100, vision 65/100, speed 82/100, and safety 65/100.
Pricing is not applicable for this self-hosted or open-weight entry. With a context window of 10,485,760 tokens, it supports large-document analysis and retrieval workflows.
Benchmark coverage is still limited for this entry, so this section focuses on published metadata and deployment fit.
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