Llama 4 Maverick
Not tested yet
Language modelActive
Llama 4 Maverick
Meta
- Released
- April 2025
- Data date
- September 8, 2026
- Intelligence
- Overall score
- Speed
- 93 tokens/sOutput throughput
- Price
- Input · Output / 1M tokens
- Input
- Text, Image
- Output
- Text
No published category-wide ranking is available for this model.
Entries 1-12 of 27. Page 1 of 3.
Published benchmarks
Each chart compares models in the same documented test and highlights the current model.
MultiNRC
Overall
What this benchmark measures: Native reasoning tasks in French, Spanish, and Chinese that were not translated from English templates.
Context: Three languages counter English-only evaluation, but they do not represent global language coverage.
Higher is better10 modelsLlama 4 Maverick: Rank 10 of 10Data date: August 26, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- scale-multinrc-native-languages
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 10
- Methodology and context
- Native, non-translated reasoning tasks with automatic evaluation.. Source model ID: curated/llama-4-maverick. Source model name: Llama 4 Maverick. Provider reported by source: Meta. Evaluator: Scale AI. Dataset type: public. Attempts: pass@1. Score display: 8.44% ± 1.68. Source ID: scale-ai. Evidence capture ID: curated-scale-ai-2026-08-26-bc7fb4bc0d9a. Source payload hash: bc7fb4bc0d9ad4757d46043b7c57b0b056967f2b0062249a99a3f0b616b95e23. Parser version: curated-v1. Imported at: 2026-09-04
PRBench Finance
Overall
What this benchmark measures: 600 realistic finance questions with weighted criteria, including a 300-question hard subset.
Context: An o4-mini judge scores the responses, so domain correctness and operational reliability remain separate questions.
Higher is better16 modelsLlama 4 Maverick: Rank 16 of 16Data date: August 26, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- scale-prbench-finance-full
- Metric
- weighted rubric score
- Scale
- 0-100
- Participants
- 16
- Methodology and context
- 600 finance tasks with task-specific rubrics and o4-mini as judge.. Source model ID: curated/llama-4-maverick. Source model name: Llama 4 Maverick. Provider reported by source: Meta. Evaluator: Scale AI. Dataset type: public. Attempts: pass@1. Score display: 22.36% ± 0.42. Source ID: scale-ai. Evidence capture ID: curated-scale-ai-2026-08-26-70cdca115a0d. Source payload hash: 70cdca115a0da049a285a4ae00fcd400f49e1eea46970bf26fcd4c3374930b5c. Parser version: curated-v1. Imported at: 2026-09-04
PRBench Legal
Overall
What this benchmark measures: 500 realistic legal questions with weighted criteria across jurisdictions and practice areas.
Context: The benchmark measures professional response quality but cannot replace legal review or human accountability.
Higher is better16 modelsLlama 4 Maverick: Rank 16 of 16Data date: August 26, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- scale-prbench-legal-full
- Metric
- weighted rubric score
- Scale
- 0-100
- Participants
- 16
- Methodology and context
- 500 legal tasks with task-specific rubrics and o4-mini as judge.. Source model ID: curated/llama-4-maverick. Source model name: Llama 4 Maverick. Provider reported by source: Meta. Evaluator: Scale AI. Dataset type: public. Attempts: pass@1. Score display: 24.84% ± 0.9. Source ID: scale-ai. Evidence capture ID: curated-scale-ai-2026-08-26-f4e7b1dd0a3e. Source payload hash: f4e7b1dd0a3ecd0a1d7d7b08e33377b62d408b58c2f0c61a413a4cfec0d57c2a. Parser version: curated-v1. Imported at: 2026-09-04
TutorBench
Overall
What this benchmark measures: 1,490 tasks test adaptive explanations, feedback, and hints across six STEM subjects.
Context: A Claude 4 Sonnet judge scores weighted rubrics, so strong results do not prove safe tutoring of real learners.
Higher is better8 modelsLlama 4 Maverick: Rank 7 of 8Data date: August 26, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- scale-tutorbench-overall
- Metric
- weighted rubric score
- Scale
- 0-100
- Participants
- 8
- Methodology and context
- 1,490 tasks with weighted rubrics and Claude 4 Sonnet as judge.. Source model ID: curated/llama-4-maverick. Source model name: Llama 4 Maverick. Provider reported by source: Meta. Evaluator: Scale AI. Dataset type: public. Attempts: pass@1. Score display: 40.2% ± 1. Source ID: scale-ai. Evidence capture ID: curated-scale-ai-2026-08-26-642ef8e45495. Source payload hash: 642ef8e45495e730a3e2f2ddc114f60328e5c0c6da76f877e3b1435841792058. Parser version: curated-v1. Imported at: 2026-09-04
Vision
2 measurementsVISTA
Overall
What this benchmark measures: 758 image-text tasks combine OCR, spatial understanding, object recognition, and open-ended visual reasoning.
Context: The dataset is private and uses task-specific rubrics, making independent reproduction difficult.
Higher is better11 modelsLlama 4 Maverick: Rank 10 of 11Data date: August 26, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- scale-vista-private-overall
- Metric
- rubric score
- Scale
- 0-100
- Participants
- 11
- Methodology and context
- 758 single-turn image-text tasks with structured yes-no rubrics.. Source model ID: curated/llama-4-maverick. Source model name: Llama 4 Maverick. Provider reported by source: Meta. Evaluator: Scale AI. Dataset type: public. Attempts: pass@1. Score display: 38.33% ± 0.55. Source ID: scale-ai. Evidence capture ID: curated-scale-ai-2026-08-26-ca07b51d9088. Source payload hash: ca07b51d90881a89b710581569dec80da9f3d102bf237f2da6dbe4ad5c91b720. Parser version: curated-v1. Imported at: 2026-09-04
VisualToolBench
Overall
What this benchmark measures: 1,204 visual tasks require image manipulation, Python, web search, or calculator use with at most 20 tool calls.
Context: The score belongs to the complete multimodal tool system and cannot isolate the model alone.
Higher is better10 modelsLlama 4 Maverick: Rank 10 of 10Data date: August 26, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- scale-visual-toolbench-apr
- Metric
- average pass rate
- Scale
- 0-100
- Participants
- 10
- Methodology and context
- 1,204 tasks, six tools, and at most 20 tool calls per task.. Source model ID: curated/llama-4-maverick. Source model name: Llama 4 Maverick. Provider reported by source: Meta. Evaluator: Scale AI. Dataset type: public. Attempts: pass@1. Score display: 1.41% ± 0.25. Source ID: scale-ai. Evidence capture ID: curated-scale-ai-2026-08-26-b6f662a26398. Source payload hash: b6f662a2639828660d3c7ee001d8c431eb80967131af7ab01b3e852f4e8f899d. Parser version: curated-v1. Imported at: 2026-09-04
Measurements without matching peer values
These measurements have no matching peer values under the same test conditions. Their original values and sources remain available here.
MMMU (Show measurement, test conditions, and source)
- Source value
- 73.4
- Score
- 73.4
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:llama-4-maverick:0
- Source type
- vendor-reported
- Evaluator
- Meta Llama 4 model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Instruction-tuned table; BF16
MMMU Pro (Show measurement, test conditions, and source)
- Source value
- 59.6
- Score
- 59.6
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:llama-4-maverick:1
- Source type
- vendor-reported
- Evaluator
- Meta Llama 4 model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Instruction-tuned table; BF16
MathVista (Show measurement, test conditions, and source)
- Source value
- 73.7
- Score
- 73.7
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:llama-4-maverick:2
- Source type
- vendor-reported
- Evaluator
- Meta Llama 4 model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Instruction-tuned table; BF16
ChartQA (Show measurement, test conditions, and source)
- Source value
- 90
- Score
- 90
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:llama-4-maverick:3
- Source type
- vendor-reported
- Evaluator
- Meta Llama 4 model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Instruction-tuned table; BF16
DocVQA (Show measurement, test conditions, and source)
- Source value
- 94.4
- Score
- 94.4
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:llama-4-maverick:4
- Source type
- vendor-reported
- Evaluator
- Meta Llama 4 model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Instruction-tuned table; BF16
LiveCodeBench (Show measurement, test conditions, and source)
- Source value
- 43.4
- Score
- 43.4
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:llama-4-maverick:5
- Source type
- vendor-reported
- Evaluator
- Meta Llama 4 model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Instruction-tuned table; BF16
Recorded measurement details
Every observation retains its source value and published test conditions.
MultiNRC: Overall (Show measurement, test conditions, and source)
- Source value
- 8.44
- Score
- 8.44
- Metric
- accuracy
- Unit
- %
- Benchmark version
- French, Spanish, and Chinese release
- Category
- reasoning
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- scale-multinrc-native-languages
- Confidence interval
- 1.68
- Source type
- official-leaderboard
- Evaluator
- Scale AI
- Status
- active
- Retrieved at
- 2026-08-26
- Methodology
- Native, non-translated reasoning tasks with automatic evaluation.. Source model ID: curated/llama-4-maverick. Source model name: Llama 4 Maverick. Provider reported by source: Meta. Evaluator: Scale AI. Dataset type: public. Attempts: pass@1. Score display: 8.44% ± 1.68. Source ID: scale-ai. Evidence capture ID: curated-scale-ai-2026-08-26-bc7fb4bc0d9a. Source payload hash: bc7fb4bc0d9ad4757d46043b7c57b0b056967f2b0062249a99a3f0b616b95e23. Parser version: curated-v1. Imported at: 2026-09-04
- Comparison methodology
- Native, non-translated reasoning tasks with automatic evaluation.
PRBench Finance: Overall (Show measurement, test conditions, and source)
- Source value
- 22.36
- Score
- 22.36
- Metric
- weighted rubric score
- Unit
- %
- Benchmark version
- full finance set
- Category
- finance
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- scale-prbench-finance-full
- Confidence interval
- 0.42
- Source type
- official-leaderboard
- Evaluator
- Scale AI
- Status
- active
- Retrieved at
- 2026-08-26
- Methodology
- 600 finance tasks with task-specific rubrics and o4-mini as judge.. Source model ID: curated/llama-4-maverick. Source model name: Llama 4 Maverick. Provider reported by source: Meta. Evaluator: Scale AI. Dataset type: public. Attempts: pass@1. Score display: 22.36% ± 0.42. Source ID: scale-ai. Evidence capture ID: curated-scale-ai-2026-08-26-70cdca115a0d. Source payload hash: 70cdca115a0da049a285a4ae00fcd400f49e1eea46970bf26fcd4c3374930b5c. Parser version: curated-v1. Imported at: 2026-09-04
- Comparison methodology
- 600 finance tasks with task-specific rubrics and o4-mini as judge.
PRBench Legal: Overall (Show measurement, test conditions, and source)
- Source value
- 24.84
- Score
- 24.84
- Metric
- weighted rubric score
- Unit
- %
- Benchmark version
- full legal set
- Category
- legal
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- scale-prbench-legal-full
- Confidence interval
- 0.9
- Source type
- official-leaderboard
- Evaluator
- Scale AI
- Status
- active
- Retrieved at
- 2026-08-26
- Methodology
- 500 legal tasks with task-specific rubrics and o4-mini as judge.. Source model ID: curated/llama-4-maverick. Source model name: Llama 4 Maverick. Provider reported by source: Meta. Evaluator: Scale AI. Dataset type: public. Attempts: pass@1. Score display: 24.84% ± 0.9. Source ID: scale-ai. Evidence capture ID: curated-scale-ai-2026-08-26-f4e7b1dd0a3e. Source payload hash: f4e7b1dd0a3ecd0a1d7d7b08e33377b62d408b58c2f0c61a413a4cfec0d57c2a. Parser version: curated-v1. Imported at: 2026-09-04
- Comparison methodology
- 500 legal tasks with task-specific rubrics and o4-mini as judge.
TutorBench: Overall (Show measurement, test conditions, and source)
- Source value
- 40.2
- Score
- 40.2
- Metric
- weighted rubric score
- Unit
- %
- Benchmark version
- 1,490-task release
- Category
- education
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- scale-tutorbench-overall
- Confidence interval
- 1
- Source type
- official-leaderboard
- Evaluator
- Scale AI
- Status
- active
- Retrieved at
- 2026-08-26
- Methodology
- 1,490 tasks with weighted rubrics and Claude 4 Sonnet as judge.. Source model ID: curated/llama-4-maverick. Source model name: Llama 4 Maverick. Provider reported by source: Meta. Evaluator: Scale AI. Dataset type: public. Attempts: pass@1. Score display: 40.2% ± 1. Source ID: scale-ai. Evidence capture ID: curated-scale-ai-2026-08-26-642ef8e45495. Source payload hash: 642ef8e45495e730a3e2f2ddc114f60328e5c0c6da76f877e3b1435841792058. Parser version: curated-v1. Imported at: 2026-09-04
- Comparison methodology
- 1,490 tasks with weighted rubrics and Claude 4 Sonnet as judge.
VISTA: Overall (Show measurement, test conditions, and source)
- Source value
- 38.33
- Score
- 38.33
- Metric
- rubric score
- Unit
- %
- Benchmark version
- 758 private prompt-image pairs
- Category
- multimodal
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- scale-vista-private-overall
- Confidence interval
- 0.55
- Source type
- official-leaderboard
- Evaluator
- Scale AI
- Status
- active
- Retrieved at
- 2026-08-26
- Methodology
- 758 single-turn image-text tasks with structured yes-no rubrics.. Source model ID: curated/llama-4-maverick. Source model name: Llama 4 Maverick. Provider reported by source: Meta. Evaluator: Scale AI. Dataset type: public. Attempts: pass@1. Score display: 38.33% ± 0.55. Source ID: scale-ai. Evidence capture ID: curated-scale-ai-2026-08-26-ca07b51d9088. Source payload hash: ca07b51d90881a89b710581569dec80da9f3d102bf237f2da6dbe4ad5c91b720. Parser version: curated-v1. Imported at: 2026-09-04
- Comparison methodology
- 758 single-turn image-text tasks with structured yes-no rubrics.
VisualToolBench: Overall (Show measurement, test conditions, and source)
- Source value
- 1.41
- Score
- 1.41
- Metric
- average pass rate
- Unit
- %
- Benchmark version
- 1,204-task release
- Category
- multimodal
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- scale-visual-toolbench-apr
- Confidence interval
- 0.25
- Source type
- official-leaderboard
- Evaluator
- Scale AI
- Status
- active
- Retrieved at
- 2026-08-26
- Methodology
- 1,204 tasks, six tools, and at most 20 tool calls per task.. Source model ID: curated/llama-4-maverick. Source model name: Llama 4 Maverick. Provider reported by source: Meta. Evaluator: Scale AI. Dataset type: public. Attempts: pass@1. Score display: 1.41% ± 0.25. Source ID: scale-ai. Evidence capture ID: curated-scale-ai-2026-08-26-b6f662a26398. Source payload hash: b6f662a2639828660d3c7ee001d8c431eb80967131af7ab01b3e852f4e8f899d. Parser version: curated-v1. Imported at: 2026-09-04
- Comparison methodology
- 1,204 tasks, six tools, and at most 20 tool calls per task.
Our model tests
Community tests you can inspect
Compare how the models respond to the same prompt. Each test shows the first attempt, with no subsequent fixes to the generated code. These results do not contribute to an overall score.
Pelican on a bicycle
A community classic for free-form SVG drawing.
Prompt and test conditions
Generate an SVG of a pelican riding a bicycle
Token limit including reasoning: 8,192 tokens
Task origin (Simon Willison)Profile
Specifications and access
Published information about this model. Existing estimates are explicitly labeled.
Additional source observations
Dated documentation and model-card observations. Provider limits, native context and extended context can differ. Configuration notes retain the source wording.
- License
- Llama 4 Community LicenseSource
- Release
- 2025-04-05Source
- Parameters
- 400 BSource
- Active parameters
- 17 BSource
- Architecture
- early-fusion sparse mixture-of-expertsSource
- Context window
- 1,048,576 tokensSource
- Input
- Text, ImageSource
- Output
- Text, codeSource
- Languages
- 12Source
- Training tokens
- ~22TSource
- Knowledge cutoff
- 2024-08Source
Pricing
Published prices
Prices apply to the stated unit. Resolution, output length, and provider can change the cost.
Cost example
100 API requests
$0.06
100 requests with 1,000 input and 500 output tokens each calculate to $0.06. Input accounts for $0.02; output accounts for $0.04.
- Input price
- $0.2 / 1M tokensBase tier for each request
- Output price
- $0.8 / 1M tokensBase tier for each request
The calculation uses documented token prices and no cache discount. It excludes extra tools, tax, reasoning tokens, and further hidden output tokens.
Open sourceHead-to-head comparisons
Compare this model
Each matchup compares this model with exactly one other model from the same category.
There are no published direct comparisons for this model yet.
Evidence
Sources and data date
Every statement links to its underlying documentation or leaderboard.
- Speed
Median across serving providers. Output speed after the first streaming chunk, not total response time. Retrieved September 8, 2026.
- Price
Base API prices without caching or batch discounts. Higher context tiers and other rates are listed under Costs.
- Input
Documented modalities. Retrieved September 8, 2026.
- Output
Documented modalities. Retrieved September 8, 2026.
Research date September 8, 2026. 2 source URLs checked. This documents the inspected sources, not an exhaustive inventory of every publication.
Open evidence questions and research notes (original wording)
Not found in the inspected sources
max-output-tokens. Card does not specify a model-specific maximum output.
- Model metadataSource
- Context window dataSource
- Knowledge cutoff dataSource
- API pricingSource
- Scale AI (retrieved August 26, 2026)Source
- Scale AI (retrieved August 26, 2026)Source
- Scale AI (retrieved August 26, 2026)Source
- Scale AI (retrieved August 26, 2026)Source
- Scale AI (retrieved August 26, 2026)Source
- Scale AI (retrieved August 26, 2026)Source
- Meta Llama 4 model card (retrieved September 8, 2026)Source
- Artificial Analysis (retrieved September 8, 2026)Source
- Speed measurement methodologySource