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

Llama 3.2 11B Instruct
Meta
Llama 3.2 11B Instruct is a multimodal language model developed by Meta. It achieves strong performance with an average score of 63.6% across 11 benchmarks. It excels particularly in AI2D (91.1%), DocVQA (88.4%), ChartQA (83.4%). It supports a 256K token context window for handling large documents. 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 2024, it represents Meta's latest advancement in AI technology.

Phi-3.5-vision-instruct
Microsoft
Phi-3.5-vision-instruct is a multimodal language model developed by Microsoft. It achieves strong performance with an average score of 68.3% across 9 benchmarks. It excels particularly in ScienceQA (91.3%), POPE (86.1%), MMBench (81.9%). The model shows particular specialization in general tasks with an average performance of 75.9%. 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 2024, it represents Microsoft's latest advancement in AI technology.

Phi-3.5-vision-instruct
Microsoft
2024-08-23

Llama 3.2 11B Instruct
Meta
2024-09-25
1 month newer
Performance Metrics
Context window and performance specifications

Llama 3.2 11B Instruct

Phi-3.5-vision-instruct
Average performance across 4 common benchmarks

Llama 3.2 11B Instruct

Phi-3.5-vision-instruct
Performance comparison across key benchmark categories

Llama 3.2 11B Instruct

Phi-3.5-vision-instruct
Llama 3.2 11B Instruct
2023-12-31
Provider Availability & Performance
Available providers and their performance metrics

Llama 3.2 11B Instruct
Sambanova
Together
DeepInfra
Fireworks
Groq
Bedrock

Phi-3.5-vision-instruct

Llama 3.2 11B Instruct

Phi-3.5-vision-instruct