Model Comparison

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

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.

OpenAI

o3

OpenAI

o3 is a multimodal language model developed by OpenAI. It achieves strong performance with an average score of 65.3% across 19 benchmarks. It excels particularly in AIME 2024 (91.6%), ARC-AGI (88.0%), MathVista (86.8%). The model shows particular specialization in vision tasks with an average performance of 76.7%. It supports a 300K token context window for handling large documents. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents OpenAI's latest advancement in AI technology.

Meta

Llama 4 Scout

Meta

2025-04-05

OpenAI

o3

OpenAI

2025-04-16

11 days newer

Pricing Comparison

Cost per million tokens (USD)

Meta

Llama 4 Scout

$9.62 cheaper
Input:$0.08
Output:$0.30
OpenAI

o3

Input:$2.00
Output:$8.00

Performance Metrics

Context window and performance specifications

Meta

Llama 4 Scout

Larger context
Max Context:20.0M
Parameters:109.0B
OpenAI

o3

Max Context:300.0K

Average performance across 3 common benchmarks

Meta

Llama 4 Scout

Average Score:65.8%
OpenAI

o3

+18.6%
Average Score:84.3%

Performance comparison across key benchmark categories

Meta

Llama 4 Scout

vision
+5.2%
81.9%
math
+19.2%
70.5%
general
66.3%
OpenAI

o3

vision
76.7%
math
51.3%
general
+1.2%
67.5%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

o3

2024-05-31

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

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
OpenAI

o3

1 providers

OpenAI

Throughput: 50 tok/s
Latency: 20ms
Meta

Llama 4 Scout

Avg Score:65.8%
Providers:6
OpenAI

o3

+18.6%
Avg Score:84.3%
Providers:1