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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 3n E4B Instructed

Google

Gemma 3n E4B Instructed is a multimodal language model developed by Google. The model shows competitive results across 18 benchmarks. Notable strengths include HumanEval (75.0%), MGSM (67.0%), MMLU (64.9%). The model is available through 1 API provider. 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-V3.1

DeepSeek

2025-01-10

Google

Gemma 3n E4B Instructed

Google

2025-06-26

5 months newer

Pricing Comparison

Cost per million tokens (USD)

DeepSeek

DeepSeek-V3.1

$58.73 cheaper
Input:$0.27
Output:$1.00
Google

Gemma 3n E4B Instructed

Input:$20.00
Output:$40.00

Performance Metrics

Context window and performance specifications

DeepSeek

DeepSeek-V3.1

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

Gemma 3n E4B Instructed

Max Context:64.0K
Parameters:8.0B

Average performance across 3 common benchmarks

DeepSeek

DeepSeek-V3.1

+38.2%
Average Score:63.3%
Google

Gemma 3n E4B Instructed

Average Score:25.1%

Performance comparison across key benchmark categories

DeepSeek

DeepSeek-V3.1

general
+12.7%
57.3%
code
+17.6%
56.5%
math
+2.9%
41.6%
Google

Gemma 3n E4B Instructed

general
44.6%
code
38.9%
math
38.8%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Gemma 3n E4B Instructed

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-V3.1

2 providers

DeepInfra

Novita

Google

Gemma 3n E4B Instructed

1 providers

Together

Throughput: 42.09 tok/s
Latency: 0.43ms
DeepSeek

DeepSeek-V3.1

+38.2%
Avg Score:63.3%
Providers:2
Google

Gemma 3n E4B Instructed

Avg Score:25.1%
Providers:1