Model Comparison

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

OpenAI

GPT-4 Turbo

OpenAI

GPT-4 Turbo is a language model developed by OpenAI. It achieves strong performance with an average score of 78.1% across 6 benchmarks. It excels particularly in MGSM (88.5%), HumanEval (87.1%), MMLU (86.5%). It supports a 132K token context window for handling large documents. The model is available through 2 API providers. Released in 2024, it represents OpenAI'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.

OpenAI

GPT-4 Turbo

OpenAI

2024-04-09

Meta

Llama 4 Scout

Meta

2025-04-05

12 months newer

Pricing Comparison

Cost per million tokens (USD)

OpenAI

GPT-4 Turbo

Input:$10.00
Output:$30.00
Meta

Llama 4 Scout

$39.62 cheaper
Input:$0.08
Output:$0.30

Performance Metrics

Context window and performance specifications

OpenAI

GPT-4 Turbo

Max Context:132.1K
Meta

Llama 4 Scout

Larger context
Max Context:20.0M
Parameters:109.0B

Average performance across 4 common benchmarks

OpenAI

GPT-4 Turbo

+4.5%
Average Score:73.9%
Meta

Llama 4 Scout

Average Score:69.4%

Performance comparison across key benchmark categories

OpenAI

GPT-4 Turbo

code
+36.8%
87.1%
math
+10.0%
80.5%
general
+7.2%
73.5%
Meta

Llama 4 Scout

code
50.3%
math
70.5%
general
66.3%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

GPT-4 Turbo

2023-12-31

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

OpenAI

GPT-4 Turbo

2 providers

Azure

Throughput: 97 tok/s
Latency: 0.6ms

OpenAI

Throughput: 100 tok/s
Latency: 0.5ms
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

GPT-4 Turbo

+4.5%
Avg Score:73.9%
Providers:2
Meta

Llama 4 Scout

Avg Score:69.4%
Providers:6