Model Comparison
Comprehensive side-by-side analysis of model capabilities and performance
DeepSeek R1 Zero
DeepSeek
DeepSeek R1 Zero is a language model developed by DeepSeek. It achieves strong performance with an average score of 76.5% across 4 benchmarks. It excels particularly in MATH-500 (95.9%), AIME 2024 (86.7%), GPQA (73.3%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents DeepSeek's latest advancement in AI technology.
Llama 3.2 90B Instruct
Meta
Llama 3.2 90B Instruct is a multimodal language model developed by Meta. It achieves strong performance with an average score of 71.3% across 13 benchmarks. It excels particularly in AI2D (92.3%), DocVQA (90.1%), MGSM (86.9%). It supports a 256K token context window for handling large documents. The model is available through 5 API providers. 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 Meta's latest advancement in AI technology.
Llama 3.2 90B Instruct
Meta
2024-09-25
DeepSeek R1 Zero
DeepSeek
2025-01-20
3 months newer
Performance Metrics
Context window and performance specifications
DeepSeek R1 Zero
Llama 3.2 90B Instruct
Average performance across 1 common benchmarks
DeepSeek R1 Zero
Llama 3.2 90B Instruct
Performance comparison across key benchmark categories
DeepSeek R1 Zero
Llama 3.2 90B Instruct
Provider Availability & Performance
Available providers and their performance metrics
DeepSeek R1 Zero
Llama 3.2 90B Instruct
Together
Hyperbolic
DeepInfra
Fireworks
Bedrock
DeepSeek R1 Zero
Llama 3.2 90B Instruct