Model Comparison

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

DeepSeek

DeepSeek-R1-0528

DeepSeek

DeepSeek-R1-0528 is a language model developed by DeepSeek. It achieves strong performance with an average score of 68.1% across 16 benchmarks. It excels particularly in MMLU-Redux (93.4%), AIME 2024 (91.4%), AIME 2025 (87.5%). It supports a 262K token context window for handling large documents. The model is available through 3 API providers. Released in 2025, it represents DeepSeek's latest advancement in AI technology.

Google

Gemma 3n E4B

Google

Gemma 3n E4B is a multimodal language model developed by Google. It achieves strong performance with an average score of 64.6% across 11 benchmarks. It excels particularly in ARC-E (81.6%), BoolQ (81.6%), PIQA (81.0%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Google's latest advancement in AI technology.

DeepSeek

DeepSeek-R1-0528

DeepSeek

2025-05-28

Google

Gemma 3n E4B

Google

2025-06-26

29 days newer

Performance Metrics

Context window and performance specifications

DeepSeek

DeepSeek-R1-0528

Larger context
Max Context:262.1K
Parameters:671.0B
Google

Gemma 3n E4B

Max Context:-
Parameters:8.0B

Performance comparison across key benchmark categories

DeepSeek

DeepSeek-R1-0528

general
+9.5%
69.2%
Google

Gemma 3n E4B

general
59.6%
Knowledge Cutoff
Training data recency comparison

Gemma 3n E4B

2024-06-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

DeepSeek

DeepSeek-R1-0528

3 providers

DeepInfra

Throughput: 45.04 tok/s
Latency: 0.61ms

Novita

Throughput: 37.96 tok/s
Latency: 1.18ms

DeepSeek

Throughput: 9 tok/s
Latency: 0.3ms
Google

Gemma 3n E4B

0 providers
DeepSeek

DeepSeek-R1-0528

Avg Score:0.0%
Providers:3
Google

Gemma 3n E4B

Avg Score:0.0%
Providers:0