Model Comparison

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

DeepSeek

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.

Google

Gemma 3 4B

Google

Gemma 3 4B is a multimodal language model developed by Google. The model shows competitive results across 26 benchmarks. It excels particularly in IFEval (90.2%), GSM8k (89.2%), DocVQA (75.8%). It supports a 262K token context window for handling large documents. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Google's latest advancement in AI technology.

Google

Gemma 3 4B

Google

2025-03-12

DeepSeek

DeepSeek-V3.2-Exp

DeepSeek

2025-09-29

6 months newer

Pricing Comparison

Cost per million tokens (USD)

DeepSeek

DeepSeek-V3.2-Exp

Input:$0.27
Output:$0.41
Google

Gemma 3 4B

$0.62 cheaper
Input:$0.02
Output:$0.04

Performance Metrics

Context window and performance specifications

DeepSeek

DeepSeek-V3.2-Exp

Max Context:229.4K
Parameters:685.0B
Google

Gemma 3 4B

Larger context
Max Context:262.1K
Parameters:4.0B

Average performance across 36 common benchmarks

DeepSeek

DeepSeek-V3.2-Exp

Average Score:25.7%
Google

Gemma 3 4B

+12.6%
Average Score:38.3%

Performance comparison across key benchmark categories

DeepSeek

DeepSeek-V3.2-Exp

factuality
+60.0%
97.1%
math
+22.0%
86.5%
code
+2.7%
64.3%
general
+17.7%
62.1%
Google

Gemma 3 4B

factuality
37.0%
math
64.5%
code
61.5%
general
44.3%
Knowledge Cutoff
Training data recency comparison

Gemma 3 4B

2024-08-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

DeepSeek

DeepSeek-V3.2-Exp

2 providers

Novita

ZeroEval

Throughput: 100 tok/s
Latency: 0.7ms
Google

Gemma 3 4B

1 providers

DeepInfra

Throughput: 33 tok/s
Latency: 0.2ms
DeepSeek

DeepSeek-V3.2-Exp

Avg Score:25.7%
Providers:2
Google

Gemma 3 4B

+12.6%
Avg Score:38.3%
Providers:1