Meta·#232 of 352 on the current board·cheaper than #226 GPT-4 Turbo
Llama 4 Scout is a language model from Meta. It ranks #232 of 352 on ModelCap's current board, with an Index score of 31.3, measured on 3 public benchmarks. Its score range of 26.5–36.1 spans positions #196–#253. It is listed at $0.10 per million input tokens and $0.30 per million output tokens across 2 providers. It reads up to 1.3M tokens of context, and its weights are downloadable after an access request.
Figures as of 6 Nov 2026, 20:32 UTC · download the public dataset · methodology
Provider economics and telemetry published by the Hugging Face Router. These are operational signals, not benchmark results.
Structured rows reported in this exact model repository at the pinned revision below. They are the publisher talking about itself: never measured evidence, never a score input on their own. They remain quarantined until dataset revision, harness, configuration and identity pass ModelCap’s independent admission review.
BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.
These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.
The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.
Not yet published: a link to the licence terms, pinned evaluation dataset versions.
A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.
Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.
OpenRouter weekly popularity across the full model catalogue.
Independent providers versus the model's open or closed cohort, weighted by uptime.
Hugging Face 30-day downloads for open models; neutral for closed models.
Time since first public availability, on a six-month half-life.
meta-llama/llama-4-scoutOpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata
Gated access. The weights are hosted behind an access request or acceptance step. Review the publisher's access requirements and license before use or redistribution.
Models within 3 places of #232 on the ModelCap Index.
Index score within 3 points of, or above, this model's, with a lower listed blended price (3:1 input:output).
The same publisher's other current models with a public Index position.
Llama 4 Scout holds ModelCap Index position #232 of 352 ranked language models as of 6 November 2026, with an Index score of 31.3 (interval 26.5–36.1); evidence: measured. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.
Llama 4 Scout is listed at $0.10 per 1M input tokens and $0.30 per 1M output tokens as of 6 November 2026; the lowest output price among 2 providers is $0.24 on DeepInfra. Prices come from the OpenRouter catalogue and re-observe on every refresh. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply $0.35 total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.
Llama 4 Scout has a published context window of 1.3M tokens (1,310,720). The snapshot lists a 16,384 token catalogue-declared route output cap. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. The providers table lists each endpoint's context limit.
Gated access (llama4). The weights are hosted behind an access request or acceptance step. Review the publisher's access requirements and license before use or redistribution. The repository is meta-llama/Llama-4-Scout-17B-16E-Instruct on Hugging Face.
2 providers serve Llama 4 Scout through OpenRouter as of 6 November 2026: DeepInfra and Google. Each provider's price, context limit, quantization and measured uptime are in the providers table above.
Llama 4 Scout has published results on 4 public boards tracked by ModelCap as of 6 November 2026: Arena text 1321 (#262 of 419), Arena coding 1362 (#257 of 414), ARC-AGI-2 0.0% (#263 of 281) and BFCL V4 28.1 (#54 of 83). Each board page ranks every tracked model on that benchmark. The ModelCap Index scores the results its methodology admits, with published uncertainty, and shows reference boards without scoring them.
Llama 4 Scout ranks #232 (Index 31.3) and Llama 3.3 70B Instruct ranks #235 (Index 30.8) on the ModelCap Index as of 6 November 2026. The head-to-head page lines up their benchmarks, listed prices, context windows and provider counts side by side.
Llama 4 Scout first appeared in the catalogue on 5 Apr 2025, with a published knowledge cutoff of 2024-08-31. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.