Model Comparison

DeepSeek-R1-0528 vs Gemma 3n E4B Instructed LiteRT Preview

DeepSeek-R1-0528 significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

DeepSeek-R1-0528 outperforms in 4 benchmarks (AIME 2025, GPQA, LiveCodeBench, MMLU-Pro), while Gemma 3n E4B Instructed LiteRT Preview is better at 0 benchmarks.

DeepSeek-R1-0528 significantly outperforms across most benchmarks.

Fri May 01 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Fri May 01 2026 • llm-stats.com
DeepSeek
DeepSeek-R1-0528
Input tokens$0.50
Output tokens$2.15
Best providerDeepinfra
Google
Gemma 3n E4B Instructed LiteRT Preview
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

669.1B diff

DeepSeek-R1-0528 has 669.1B more parameters than Gemma 3n E4B Instructed LiteRT Preview, making it 35030.9% larger.

DeepSeek
DeepSeek-R1-0528
671.0Bparameters
Google
Gemma 3n E4B Instructed LiteRT Preview
1.9Bparameters
671.0B
DeepSeek-R1-0528
1.9B
Gemma 3n E4B Instructed LiteRT Preview

Context Window

Maximum input and output token capacity

Only DeepSeek-R1-0528 specifies input context (131,072 tokens). Only DeepSeek-R1-0528 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-R1-0528
Input131,072 tokens
Output131,072 tokens
Google
Gemma 3n E4B Instructed LiteRT Preview
Input- tokens
Output- tokens
Fri May 01 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemma 3n E4B Instructed LiteRT Preview supports multimodal inputs, whereas DeepSeek-R1-0528 does not.

Gemma 3n E4B Instructed LiteRT Preview can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-R1-0528

Text
Images
Audio
Video

Gemma 3n E4B Instructed LiteRT Preview

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-R1-0528 is licensed under MIT, while Gemma 3n E4B Instructed LiteRT Preview uses Gemma.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek-R1-0528

MIT

Open weights

Gemma 3n E4B Instructed LiteRT Preview

Gemma

Open weights

Release Timeline

When each model was launched

DeepSeek-R1-0528 was released on 2025-05-28, while Gemma 3n E4B Instructed LiteRT Preview was released on 2025-05-20.

DeepSeek-R1-0528 is 0 month newer than Gemma 3n E4B Instructed LiteRT Preview.

DeepSeek-R1-0528

May 28, 2025

11 months ago

1w newer
Gemma 3n E4B Instructed LiteRT Preview

May 20, 2025

11 months ago

Knowledge Cutoff

When training data ends

Gemma 3n E4B Instructed LiteRT Preview has a documented knowledge cutoff of 2024-06-01, while DeepSeek-R1-0528's cutoff date is not specified.

We can confirm Gemma 3n E4B Instructed LiteRT Preview's training data extends to 2024-06-01, but cannot make a direct comparison without DeepSeek-R1-0528's cutoff date.

DeepSeek-R1-0528

—

Gemma 3n E4B Instructed LiteRT Preview

Jun 2024

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (131,072 tokens)
Higher AIME 2025 score (87.5% vs 11.6%)
Higher GPQA score (81.0% vs 23.7%)
Higher LiveCodeBench score (73.3% vs 13.2%)
Higher MMLU-Pro score (85.0% vs 50.6%)
Google
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-R1-0528
Google
Gemma 3n E4B Instructed LiteRT Preview

FAQ

Common questions about DeepSeek-R1-0528 vs Gemma 3n E4B Instructed LiteRT Preview

DeepSeek-R1-0528 significantly outperforms across most benchmarks. DeepSeek-R1-0528 is made by DeepSeek and Gemma 3n E4B Instructed LiteRT Preview is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek-R1-0528 scores MMLU-Redux: 93.4%, SimpleQA: 92.3%, AIME 2024: 91.4%, AIME 2025: 87.5%, MMLU-Pro: 85.0%. Gemma 3n E4B Instructed LiteRT Preview scores ARC-E: 81.6%, BoolQ: 81.6%, PIQA: 81.0%, HellaSwag: 78.6%, HumanEval: 75.0%.
DeepSeek-R1-0528 supports 131K tokens and Gemma 3n E4B Instructed LiteRT Preview supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include multimodal support (no vs yes), licensing (MIT vs Gemma). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-R1-0528 is developed by DeepSeek and Gemma 3n E4B Instructed LiteRT Preview is developed by Google.