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.

Alibaba

Qwen2.5 VL 32B Instruct

Alibaba

Qwen2.5 VL 32B Instruct is a multimodal language model developed by Alibaba. It achieves strong performance with an average score of 63.6% across 28 benchmarks. It excels particularly in DocVQA (94.8%), Android Control Low_EM (93.3%), HumanEval (91.5%). The model shows particular specialization in code tasks with an average performance of 87.8%. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Alibaba's latest advancement in AI technology.

Alibaba

Qwen2.5 VL 32B Instruct

Alibaba

2025-02-28

Meta

Llama 4 Scout

Meta

2025-04-05

1 month newer

Performance Metrics

Context window and performance specifications

Meta

Llama 4 Scout

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

Qwen2.5 VL 32B Instruct

Max Context:-
Parameters:33.5B

Average performance across 7 common benchmarks

Meta

Llama 4 Scout

Average Score:70.4%
Alibaba

Qwen2.5 VL 32B Instruct

+4.5%
Average Score:74.9%

Performance comparison across key benchmark categories

Meta

Llama 4 Scout

code
50.3%
vision
+17.9%
81.9%
math
+5.4%
70.5%
general
+6.2%
66.3%
Alibaba

Qwen2.5 VL 32B Instruct

code
+37.4%
87.8%
vision
64.0%
math
65.1%
general
60.1%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores

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
Alibaba

Qwen2.5 VL 32B Instruct

0 providers
Meta

Llama 4 Scout

Avg Score:70.4%
Providers:6
Alibaba

Qwen2.5 VL 32B Instruct

+4.5%
Avg Score:74.9%
Providers:0