Model profile
Llama 4 Scout
Evidence coverage
18 of 321 tracked benchmarks are published. 1 is verified and 17 provisional. 7 of 8 categories are measured.
- Published / tracked
- 18 / 321
- Verified
- 1
- Provisional
- 17
- Categories with evidence
- 7 / 8
Evidence by category
- Agentic4 benchmarksReported
- Coding2 benchmarksReported
- Reasoning2 benchmarksReported
- Knowledge6 benchmarksReported
- Math1 benchmarkVerified
- Multilingual0 benchmarksNot measured
- Multimodal2 benchmarksReported
- Inst. Following1 benchmarkReported
Llama 4 Scout ranks #174 out of 200 models on the public leaderboard with an overall score of 39.87/100. It also ranks #80 out of 99 on the verified leaderboard. While not a frontier model, it offers specific advantages depending on the use case.
Llama 4 Scout is a open weight model with a 10M token context window. It processes queries without explicit chain-of-thought reasoning, offering faster response times and lower token usage.
This profile currently has 18 of 321 tracked benchmarks. BenchLM only exposes non-generated benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.
Its strongest category is Agentic (#107), while its weakest is Coding (#110). This performance profile makes it particularly useful for coding agents, browser research, and computer-use workflows.
Peer position
Exact provisional scores and ranks for the closest listed peers. A score can appear before a model clears the evidence threshold for a rank, so equal scores can have different rank states.
Range 39.52–40.43
- Grok 3 [Beta]xAICompare#17140.43Grok 3 [Beta] is #171 with a score of 40.43.
- Ministral 3 8B (Reasoning)MistralCompare#17240.38Ministral 3 8B (Reasoning) is #172 with a score of 40.38.
- Mistral 7B v0.3MistralCompare#17339.9Mistral 7B v0.3 is #173 with a score of 39.9.
- Llama 4 ScoutCurrent modelMeta#17439.87Llama 4 Scout is #174 with a score of 39.87.
- Qwen2.5-VL-32BAlibabaCompare#17539.85Qwen2.5-VL-32B is #175 with a score of 39.85.
- Llama 4 BehemothMetaCompare#17639.8Llama 4 Behemoth is #176 with a score of 39.8.
- Ministral 3 3B (Reasoning)MistralCompare#17739.52Ministral 3 3B (Reasoning) is #177 with a score of 39.52.
Category percentile
More
Relative position among models eligible for each sourced category. A higher percentile means a stronger position within that category's ranked cohort; 100 is highest.
- Agentic10%Eligible cohort rank #107 of 119Category score 35.0
- Coding10%Eligible cohort rank #110 of 122Category score 36.3
Category evidence
Scores and ranks appear only where this model has published benchmark evidence. Categories without displayable source records remain not measured.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticRank #107 of 119Percentile 10thWeight 22%4 benchmarksReported | 35.0 | #107 of 119 | 10th | 22% | 4 benchmarks | Reported |
| CodingRank #110 of 122Percentile 10thWeight 20%2 benchmarksReported | 36.3 | #110 of 122 | 10th | 20% | 2 benchmarks | Reported |
| ReasoningRank Not rankedWeight 17%2 benchmarksReported | 64.9 | Not ranked | Not available | 17% | 2 benchmarks | Reported |
| KnowledgeRank Not rankedWeight 12%6 benchmarksReported | 27.5 | Not ranked | Not available | 12% | 6 benchmarks | Reported |
| MathRank Not rankedWeight 5%1 benchmarkVerified | 25.4 | Not ranked | Not available | 5% | 1 benchmark | Verified |
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | Not ranked | Not available | 7% | 0 benchmarks | Not measured |
| MultimodalRank Not rankedWeight 12%2 benchmarksReported | 58.0 | Not ranked | Not available | 12% | 2 benchmarks | Reported |
| Inst. FollowingRank Not rankedWeight 5%1 benchmarkReported | 67.2 | Not ranked | Not available | 5% | 1 benchmark | Reported |
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
Chatbot Arena performance
Scroll horizontally to inspect confidence intervals and vote counts.
| View | Elo | Confidence interval | Votes |
|---|---|---|---|
| Text Overall | 1322 | Not available | Not available |
Benchmark Details
Rows below have a displayable published verification record. Each source link and provenance note remains in the page HTML while its category is closed. Source-unverified manual rows and generated rows stay hidden.
Agentic4 benchmarks
Artificial Analysis Agentic Index
τ²-Bench Tool-Agent-User Evaluation
GDPval-AA normalized
Coding2 benchmarks
Artificial Analysis Coding Index
Artificial Analysis SciCode
Reasoning2 benchmarks
Artificial Analysis Long Context Reasoning
Critical Physics Tasks
Knowledge6 benchmarks
Artificial Analysis GPQA Diamond
Artificial Analysis Humanity's Last Exam
Artificial Analysis Omniscience Index
Artificial Analysis Omniscience Accuracy
Artificial Analysis Omniscience Hallucination Rate
Math1 benchmark
FrontierMath v2 Tiers 1-3
Multimodal2 benchmarks
Artificial Analysis MMMU-Pro
Design Arena Website Elo
Inst. Following1 benchmark
Artificial Analysis IFBench
Frequently Asked Questions
How does Llama 4 Scout perform overall in AI benchmarks?
Llama 4 Scout has 18 published benchmark scores on BenchLM, but it does not yet have enough non-generated coverage to receive a global overall rank.
Is Llama 4 Scout good for knowledge and understanding?
Llama 4 Scout has visible benchmark coverage in knowledge and understanding, but BenchLM does not currently assign it a global category rank there.
Is Llama 4 Scout good for coding and programming?
Llama 4 Scout ranks #110 out of 122 models in coding and programming benchmarks with an average score of 36.3. There are stronger options in this category.
Is Llama 4 Scout good for mathematics?
Llama 4 Scout has visible benchmark coverage in mathematics, but BenchLM does not currently assign it a global category rank there.
Is Llama 4 Scout good for reasoning and logic?
Llama 4 Scout has visible benchmark coverage in reasoning and logic, but BenchLM does not currently assign it a global category rank there.
Is Llama 4 Scout good for agentic tool use and computer tasks?
Llama 4 Scout ranks #107 out of 119 models in agentic tool use and computer tasks benchmarks with an average score of 35. There are stronger options in this category.
Is Llama 4 Scout good for multimodal and grounded tasks?
Llama 4 Scout has visible benchmark coverage in multimodal and grounded tasks, but BenchLM does not currently assign it a global category rank there.
Is Llama 4 Scout good for instruction following?
Llama 4 Scout has visible benchmark coverage in instruction following, but BenchLM does not currently assign it a global category rank there.
Is Llama 4 Scout open source?
Yes, Llama 4 Scout is an open weight model created by Meta, meaning it can be downloaded and run locally or fine-tuned for specific use cases.
Does Llama 4 Scout have full benchmark coverage on BenchLM?
Not yet. Llama 4 Scout currently has 18 published benchmark scores out of the 321 benchmarks BenchLM tracks. BenchLM only exposes non-generated public benchmark rows, so missing categories stay blank until a sourced evaluation is available.
What is the context window size of Llama 4 Scout?
Llama 4 Scout has a published context window of 10M, which determines how much text it can process in a single interaction.
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