Model Comparison

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

DeepSeek-V3.2-Exp

DeepSeek

DeepSeek-V3.2-Exp is a language model developed by DeepSeek. It achieves strong performance with an average score of 66.1% across 14 benchmarks. It excels particularly in SimpleQA (97.1%), AIME 2025 (89.3%), MMLU-Pro (85.0%). It supports a 229K token context window for handling large documents. The model is available through 2 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, 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-V3.2-Exp

DeepSeek

2025-09-29

1 year newer

Performance Metrics

Context window and performance specifications

DeepSeek-V3.2-Exp

Larger context

Max Context:229.4K

Parameters:685.0B

Gemma 2 9B

Max Context:-

Parameters:9.2B

Average performance across 30 common benchmarks

DeepSeek-V3.2-Exp

Average Score:30.8%

Gemma 2 9B

+3.6%

Average Score:34.5%

Performance comparison across key benchmark categories

DeepSeek-V3.2-Exp

math

+33.9%

86.5%

general

62.1%

code

+15.8%

64.3%

Gemma 2 9B

math

52.6%

general

+4.3%

66.4%

code

48.5%

Provider Availability & Performance

Available providers and their performance metrics

DeepSeek-V3.2-Exp

2 providers

Novita

ZeroEval

Throughput: 100 tok/s

Latency: 0.7ms

Gemma 2 9B

0 providers

DeepSeek-V3.2-Exp

Avg Score:30.8%

Providers:2

Gemma 2 9B

+3.6%

Avg Score:34.5%

Providers:0