Model Comparison

DeepSeek R1 Zero vs Gemma 3 27B

DeepSeek R1 Zero significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DeepSeek R1 Zero outperforms in 2 benchmarks (GPQA, LiveCodeBench), while Gemma 3 27B is better at 0 benchmarks.

DeepSeek R1 Zero significantly outperforms across most benchmarks.

Mon May 25 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

644.0B diff

DeepSeek R1 Zero has 644.0B more parameters than Gemma 3 27B, making it 2385.2% larger.

DeepSeek
DeepSeek R1 Zero
671.0Bparameters
Google
Gemma 3 27B
27.0Bparameters
671.0B
DeepSeek R1 Zero
27.0B
Gemma 3 27B

Context Window

Maximum input and output token capacity

Only Gemma 3 27B specifies input context (131,072 tokens). Only Gemma 3 27B specifies output context (131,072 tokens).

DeepSeek
DeepSeek R1 Zero
Input- tokens
Output- tokens
Google
Gemma 3 27B
Input131,072 tokens
Output131,072 tokens
Mon May 25 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemma 3 27B supports multimodal inputs, whereas DeepSeek R1 Zero does not.

Gemma 3 27B can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek R1 Zero

Text
Images
Audio
Video

Gemma 3 27B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek R1 Zero is licensed under MIT, while Gemma 3 27B uses Gemma.

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

DeepSeek R1 Zero

MIT

Open weights

Gemma 3 27B

Gemma

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Zero was released on 2025-01-20, while Gemma 3 27B was released on 2025-03-12.

Gemma 3 27B is 2 months newer than DeepSeek R1 Zero.

DeepSeek R1 Zero

Jan 20, 2025

1.3 years ago

Gemma 3 27B

Mar 12, 2025

1.2 years ago

1mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

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Key Takeaways

DeepSeek
Higher GPQA score (73.3% vs 42.4%)
Higher LiveCodeBench score (50.0% vs 29.7%)
Google
Larger context window (131,072 tokens)
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Zero
Google
Gemma 3 27B

FAQ

Common questions about DeepSeek R1 Zero vs Gemma 3 27B.

Which is better, DeepSeek R1 Zero or Gemma 3 27B?

DeepSeek R1 Zero significantly outperforms across most benchmarks. DeepSeek R1 Zero is made by DeepSeek and Gemma 3 27B is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek R1 Zero compare to Gemma 3 27B in benchmarks?

DeepSeek R1 Zero scores MATH-500: 95.9%, AIME 2024: 86.7%, GPQA: 73.3%, LiveCodeBench: 50.0%. Gemma 3 27B scores GSM8k: 95.9%, IFEval: 90.4%, MATH: 89.0%, HumanEval: 87.8%, BIG-Bench Hard: 87.6%.

What are the context window sizes for DeepSeek R1 Zero and Gemma 3 27B?

DeepSeek R1 Zero supports an unknown number of tokens and Gemma 3 27B supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek R1 Zero and Gemma 3 27B?

Key differences include multimodal support (no vs yes), licensing (MIT vs Gemma). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek R1 Zero and Gemma 3 27B?

DeepSeek R1 Zero is developed by DeepSeek and Gemma 3 27B is developed by Google.