Model Comparison

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

DeepSeek

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.

Google

Gemma 2 9B

Google

Gemma 2 9B is a language model developed by Google. It achieves strong performance with an average score of 64.6% across 16 benchmarks. It excels particularly in ARC-E (88.0%), BoolQ (84.2%), HellaSwag (81.9%). The model shows particular specialization in reasoning tasks with an average performance of 79.7%. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Google's latest advancement in AI technology.

Google

Gemma 2 9B

Google

2024-06-27

DeepSeek

DeepSeek VL2

DeepSeek

2024-12-13

5 months newer

Performance Metrics

Context window and performance specifications

DeepSeek

DeepSeek VL2

Larger context
Max Context:258.6K
Parameters:27.0B
Google

Gemma 2 9B

Max Context:-
Parameters:9.2B

Performance comparison across key benchmark categories

DeepSeek

DeepSeek VL2

general
+3.6%
69.9%
math
+10.2%
62.8%
Google

Gemma 2 9B

general
66.4%
math
52.6%

Provider Availability & Performance

Available providers and their performance metrics

DeepSeek

DeepSeek VL2

1 providers

Replicate

Throughput: 22 tok/s
Latency: 0.5ms
Google

Gemma 2 9B

0 providers
DeepSeek

DeepSeek VL2

Avg Score:0.0%
Providers:1
Google

Gemma 2 9B

Avg Score:0.0%
Providers:0