Model Comparison

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

DeepSeek-V3

DeepSeek

DeepSeek-V3 is a language model developed by DeepSeek. It achieves strong performance with an average score of 67.2% across 20 benchmarks. It excels particularly in DROP (91.6%), CLUEWSC (90.9%), MATH-500 (90.2%). It supports a 262K token context window for handling large documents. The model is available through 1 API provider. Released in 2024, it represents DeepSeek's latest advancement in AI technology.

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.

Gemma 2 9B

Google

2024-06-27

DeepSeek-V3

DeepSeek

2024-12-25

6 months newer

Performance Metrics

Context window and performance specifications

DeepSeek-V3

Larger context

Max Context:262.1K

Parameters:671.0B

Gemma 2 9B

Max Context:-

Parameters:9.2B

Average performance across 1 common benchmarks

DeepSeek-V3

+17.2%

Average Score:88.5%

Gemma 2 9B

Average Score:71.3%

Performance comparison across key benchmark categories

DeepSeek-V3

math

+37.6%

90.2%

code

+24.7%

73.2%

general

65.1%

Gemma 2 9B

math

52.6%

code

48.5%

general

+1.2%

66.4%

Benchmark Scores - Detailed View

Side-by-side comparison of all benchmark scores

Provider Availability & Performance

Available providers and their performance metrics

DeepSeek-V3

1 providers

DeepSeek

Throughput: 100 tok/s

Latency: 0.5ms

Gemma 2 9B

0 providers

DeepSeek-V3

+17.2%

Avg Score:88.5%

Providers:1

Gemma 2 9B

Avg Score:71.3%

Providers:0