Model Comparison

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

DeepSeek

DeepSeek-V2.5

DeepSeek

DeepSeek-V2.5 is a language model developed by DeepSeek. It achieves strong performance with an average score of 71.1% across 15 benchmarks. It excels particularly in GSM8k (95.1%), MT-Bench (90.2%), HumanEval (89.0%). The model is available through 3 API providers. Released in 2024, 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-V2.5

DeepSeek

2024-05-08

Google

Gemma 3n E4B

Google

2025-06-26

1 year newer

Performance Metrics

Context window and performance specifications

DeepSeek

DeepSeek-V2.5

Larger context
Max Context:16.4K
Parameters:236.0B
Google

Gemma 3n E4B

Max Context:-
Parameters:8.0B

Performance comparison across key benchmark categories

DeepSeek

DeepSeek-V2.5

general
+8.8%
68.4%
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-V2.5

3 providers

Hyperbolic

Throughput: 100 tok/s
Latency: 0.5ms

DeepInfra

Throughput: 63 tok/s
Latency: 0.5ms

DeepSeek

Throughput: 100 tok/s
Latency: 0.5ms
Google

Gemma 3n E4B

0 providers
DeepSeek

DeepSeek-V2.5

Avg Score:0.0%
Providers:3
Google

Gemma 3n E4B

Avg Score:0.0%
Providers:0