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Model Comparison

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

DeepSeek

DeepSeek-V3.1

DeepSeek

DeepSeek-V3.1 is a language model developed by DeepSeek. The model shows competitive results across 16 benchmarks. It excels particularly in SimpleQA (93.4%), MMLU-Redux (91.8%), MMLU-Pro (83.7%). The model shows particular specialization in factuality tasks with an average performance of 92.6%. It supports a 328K 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.

Google

Gemma 2 27B

Google

Gemma 2 27B is a language model developed by Google. It achieves strong performance with an average score of 69.1% across 16 benchmarks. It excels particularly in ARC-E (88.6%), HellaSwag (86.4%), BoolQ (84.8%). The model shows particular specialization in reasoning tasks with an average performance of 82.5%. 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 27B

Google

2024-06-27

DeepSeek

DeepSeek-V3.1

DeepSeek

2025-01-10

6 months newer

Performance Metrics

Context window and performance specifications

DeepSeek

DeepSeek-V3.1

Larger context
Max Context:327.7K
Parameters:671.0B
Google

Gemma 2 27B

Max Context:-
Parameters:27.2B

Performance comparison across key benchmark categories

DeepSeek

DeepSeek-V3.1

reasoning
74.9%
general
57.3%
math
41.6%
code
56.5%
Google

Gemma 2 27B

reasoning
+7.6%
82.5%
general
+12.7%
70.0%
math
+16.5%
58.1%
code
+0.0%
56.5%

Provider Availability & Performance

Available providers and their performance metrics

DeepSeek

DeepSeek-V3.1

2 providers

DeepInfra

Novita

Google

Gemma 2 27B

0 providers
DeepSeek

DeepSeek-V3.1

Avg Score:0.0%
Providers:2
Google

Gemma 2 27B

Avg Score:0.0%
Providers:0