Llama 4 Scout: benchmark scores, price and ranking

Llama 4 Scout from Meta AI ranks #435 of 743 LLMs on the LLMs Tiger aggregate benchmark score (47.4), based on 2 benchmark results captured up to 2026-10-13.

Organisation: Meta AI
Type: Open-weight / local model
Open weights: Yes
Released: 2025-04-05 (source: curated)
Cheapest API price: $0.100 in / $0.300 out per million tokens (via vercel_ai_gateway, observed 2026-10-13T20:47Z)
Aggregate rank: #435 of 743 (score 47.4)

Across the 2 benchmarks where at least ten models are scored, Llama 4 Scout is in the top 10% on 0 and in the top half on 1.

Its cheapest listed input price, $0.100 per million tokens, is lower than that of 79% of the 427 models with a listed price.

Llama 4 Scout benchmark results

Llama 4 Scout benchmark scores, ranked against all models measured on each benchmark
Benchmark	Score	Rank	Source	Captured
Epoch ECI	130	#90 of 204	Epoch AI Benchmarking Hub	2026-10-13
ARC-AGI-2	0.0%	#85 of 87	ARC Prize official leaderboard	2026-10-13

About Llama 4 Scout

Llama 4 Scout is an open-weight model that can run on your own hardware from Meta AI. It was released on 2025-04-05, according to the developer's announcement. The cheapest API listing we track charges $0.100 per million input tokens and $0.300 per million output tokens, through vercel_ai_gateway. We hold 2 benchmark results for it across 2 areas, and none is in the top tenth of its board.

Where Llama 4 Scout stands

On our aggregate score, Llama 4 Scout is #435 of 743 ranked models, around the middle of the table. Its score is 47.4; the scale is centred on 50, so it sits 2.6 points below the typical model. That beats 41% of the ranked field. Among the 28 ranked Meta AI models it is #10. The next one up is Llama 3.1-70B at 47.5. The next one down is Llama-3.2-3B-Instruct at 47.2.

Llama 4 Scout, benchmark by benchmark

Epoch ECI puts Llama 4 Scout at 130, #90 of 204. That beats 56% of the models tested, but 27 points short of Qwen 3.8 Max (156). The results either side are Claude 3.5 Sonnet (130) and GPT-4.1 nano (130). It covers Epoch Capabilities Index: Epoch's own aggregate of ~40 benchmarks. The board median is 127, so Llama 4 Scout is 2 points above it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.

ARC-AGI-2 is a weak spot. Llama 4 Scout scores 0.0%, #85 of 87, behind 97% of the models measured. The leader, GPT-6 Astra (max), reaches 95.0%. It covers abstract reasoning, ARC Prize public eval set. The board median is 22.8%, so Llama 4 Scout is 22.8 points below it. Source: ARC Prize official leaderboard, captured 2026-10-13.

Strengths and weaknesses

Llama 4 Scout has too few results on boards with ten or more models to say where it is strong or weak. Treat any single score as a data point, not a verdict.

Price and value

The median input price across the 427 priced models is $0.500 per million tokens, so Llama 4 Scout costs less than the typical listing. Models that score within 1.5 points or better and cost less: Qwen2.5-Coder-7B-Instruct ($0.010, 49.5), DeepSeek V4.1 Flash (high) ($0.010, 48.9), Qwen2.5-Coder-3B-Instruct ($0.010, 46.5). Similar scores cost more on Qwen3.8 Flash (xhigh) ($0.113) and GLM-4.5-Air ($0.125).

Release history

The Meta AI model released before it was Llama 4 Maverick (FP8) on 2025-04-05, which scores 45.6. The next one was Llama-4-Scout-17B-16E-Instruct on 2025-04-05, at 40.1.

Reading these numbers

The 2 scores on this page come from 2 sources: ARC Prize official leaderboard (1), Epoch AI Benchmarking Hub (1). 1 of them come from an official leaderboard and 1 from datasets or third-party runs. With 2 results the aggregate rank can move a lot when one new score arrives.

Models ranked nearby

#432 Gemma 4 26B A4B (47.5)
#433 GPT-5.1 (Thinking, None) (47.5)
#434 Claude 3.7 (47.4)
#436 Magistral Medium (47.4)
#437 Magistral Small (47.4)
#438 mini-SWE-agent + Gemini 3.7 Flash (47.4)