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

Command R+
Cohere
Command R+ is a language model developed by Cohere. It achieves strong performance with an average score of 74.6% across 6 benchmarks. It excels particularly in HellaSwag (88.6%), Winogrande (85.4%), MMLU (75.7%). The model shows particular specialization in reasoning tasks with an average performance of 81.7%. It supports a 256K token context window for handling large documents. The model is available through 2 API providers. Released in 2024, it represents Cohere's latest advancement in AI technology.

DeepSeek VL2
DeepSeek
DeepSeek VL2 is a multimodal language model developed by DeepSeek. It achieves strong performance with an average score of 70.9% across 14 benchmarks. It excels particularly in DocVQA (93.3%), ChartQA (86.0%), TextVQA (84.2%). The model shows particular specialization in vision tasks with an average performance of 76.7%. It supports a 259K 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 2024, it represents DeepSeek's latest advancement in AI technology.

Command R+
Cohere
2024-08-30

DeepSeek VL2
DeepSeek
2024-12-13
3 months newer
Pricing Comparison
Cost per million tokens (USD)

Command R+

DeepSeek VL2
Performance Metrics
Context window and performance specifications

Command R+

DeepSeek VL2
Performance comparison across key benchmark categories

Command R+

DeepSeek VL2
Provider Availability & Performance
Available providers and their performance metrics

Command R+
Cohere
Bedrock

DeepSeek VL2
Replicate

Command R+

DeepSeek VL2