Model Comparison

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

DeepSeek

DeepSeek R1 Distill Qwen 32B

DeepSeek

DeepSeek R1 Distill Qwen 32B is a language model developed by DeepSeek. It achieves strong performance with an average score of 74.2% across 4 benchmarks. It excels particularly in MATH-500 (94.3%), AIME 2024 (83.3%), GPQA (62.1%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. 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 R1 Distill Qwen 32B

DeepSeek

2025-01-20

6 months newer

Performance Metrics

Context window and performance specifications

DeepSeek

DeepSeek R1 Distill Qwen 32B

Larger context
Max Context:256.0K
Parameters:32.8B
Google

Gemma 2 27B

Max Context:-
Parameters:27.2B

Performance comparison across key benchmark categories

DeepSeek

DeepSeek R1 Distill Qwen 32B

math
+36.1%
94.3%
general
+2.7%
72.7%
code
+0.7%
57.2%
Google

Gemma 2 27B

math
58.1%
general
70.0%
code
56.5%

Provider Availability & Performance

Available providers and their performance metrics

DeepSeek

DeepSeek R1 Distill Qwen 32B

1 providers

DeepInfra

Throughput: 37 tok/s
Latency: 0.65ms
Google

Gemma 2 27B

0 providers
DeepSeek

DeepSeek R1 Distill Qwen 32B

Avg Score:0.0%
Providers:1
Google

Gemma 2 27B

Avg Score:0.0%
Providers:0