Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

Meta

Llama 4 Maverick

Meta

Llama 4 Maverick is a multimodal language model developed by Meta. It achieves strong performance with an average score of 71.8% across 13 benchmarks. It excels particularly in DocVQA (94.4%), MGSM (92.3%), ChartQA (90.0%). The model shows particular specialization in vision tasks with an average performance of 75.8%. With a 2.0M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 7 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Meta's latest advancement in AI technology.

Meta

Llama 4 Scout

Meta

Llama 4 Scout is a multimodal language model developed by Meta. It achieves strong performance with an average score of 67.3% across 12 benchmarks. It excels particularly in DocVQA (94.4%), MGSM (90.6%), ChartQA (88.8%). The model shows particular specialization in vision tasks with an average performance of 81.9%. With a 20.0M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 6 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Meta's latest advancement in AI technology.

Meta

Llama 4 Maverick

Meta

2025-04-05

Meta

Llama 4 Scout

Meta

2025-04-05

0 days newer

Pricing Comparison

Cost per million tokens (USD)

Meta

Llama 4 Maverick

Input:$0.17
Output:$0.60
Meta

Llama 4 Scout

$0.39 cheaper
Input:$0.08
Output:$0.30

Performance Metrics

Context window and performance specifications

Meta

Llama 4 Maverick

Max Context:2.0M
Parameters:400.0B
Meta

Llama 4 Scout

Larger context
Max Context:20.0M
Parameters:109.0B

Average performance across 12 common benchmarks

Meta

Llama 4 Maverick

+5.5%
Average Score:72.8%
Meta

Llama 4 Scout

Average Score:67.3%

Performance comparison across key benchmark categories

Meta

Llama 4 Maverick

vision
75.8%
math
+5.2%
75.7%
general
+5.2%
71.5%
code
+10.2%
60.5%
Meta

Llama 4 Scout

vision
+6.1%
81.9%
math
70.5%
general
66.3%
code
50.3%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores

Provider Availability & Performance

Available providers and their performance metrics

Meta

Llama 4 Maverick

7 providers

Sambanova

Throughput: 638.7 tok/s
Latency: 2.04ms

Together

Throughput: 97.93 tok/s
Latency: 0.2ms

DeepInfra

Throughput: 83.59 tok/s
Latency: 0.38ms

Fireworks

Throughput: 63.03 tok/s
Latency: 0.62ms

Groq

Throughput: 307.3 tok/s
Latency: 0.27ms

Novita

Throughput: 69.42 tok/s
Latency: 0.62ms

Lambda

Throughput: 93.69 tok/s
Latency: 0.65ms
Meta

Llama 4 Scout

6 providers

Together

Throughput: 106.9 tok/s
Latency: 0.54ms

DeepInfra

Throughput: 76.1 tok/s
Latency: 0.31ms

Fireworks

Throughput: 116.1 tok/s
Latency: 0.53ms

Groq

Throughput: 776.1 tok/s
Latency: 1.08ms

Novita

Throughput: 69.82 tok/s
Latency: 0.85ms

Lambda

Throughput: 139.7 tok/s
Latency: 0.43ms
Meta

Llama 4 Maverick

+5.5%
Avg Score:72.8%
Providers:7
Meta

Llama 4 Scout

Avg Score:67.3%
Providers:6