Model Comparison

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

Cohere

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

DeepSeek VL2 Tiny

DeepSeek

DeepSeek VL2 Tiny is a multimodal language model developed by DeepSeek. It achieves strong performance with an average score of 63.1% across 14 benchmarks. It excels particularly in DocVQA (88.9%), ChartQA (81.0%), OCRBench (80.9%). 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.

Cohere

Command R+

Cohere

2024-08-30

DeepSeek

DeepSeek VL2 Tiny

DeepSeek

2024-12-13

3 months newer

Performance Metrics

Context window and performance specifications

Cohere

Command R+

Larger context
Max Context:256.0K
Parameters:104.0B
DeepSeek

DeepSeek VL2 Tiny

Max Context:-
Parameters:3.0B

Performance comparison across key benchmark categories

Cohere

Command R+

general
+13.2%
75.7%
math
+17.1%
70.7%
DeepSeek

DeepSeek VL2 Tiny

general
62.5%
math
53.6%

Provider Availability & Performance

Available providers and their performance metrics

Cohere

Command R+

2 providers

Cohere

Throughput: 59 tok/s
Latency: 0.65ms

Bedrock

Throughput: 100 tok/s
Latency: 0.5ms
DeepSeek

DeepSeek VL2 Tiny

0 providers
Cohere

Command R+

Avg Score:0.0%
Providers:2
DeepSeek

DeepSeek VL2 Tiny

Avg Score:0.0%
Providers:0