Model Comparison

DeepSeek R1 Zero vs Gemma 3 12B

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 12B is better at 0 benchmarks.

DeepSeek R1 Zero significantly outperforms across most benchmarks.

Fri Apr 10 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 Apr 10 2026 • llm-stats.com
DeepSeek
DeepSeek R1 Zero
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Google
Gemma 3 12B
Input tokens$0.05
Output tokens$0.10
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

659.0B diff

DeepSeek R1 Zero has 659.0B more parameters than Gemma 3 12B, making it 5491.7% larger.

DeepSeek
DeepSeek R1 Zero
671.0Bparameters
Google
Gemma 3 12B
12.0Bparameters
671.0B
DeepSeek R1 Zero
12.0B
Gemma 3 12B

Context Window

Maximum input and output token capacity

Only Gemma 3 12B specifies input context (131,072 tokens). Only Gemma 3 12B specifies output context (131,072 tokens).

DeepSeek
DeepSeek R1 Zero
Input- tokens
Output- tokens
Google
Gemma 3 12B
Input131,072 tokens
Output131,072 tokens
Fri Apr 10 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemma 3 12B supports multimodal inputs, whereas DeepSeek R1 Zero does not.

Gemma 3 12B 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 12B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek R1 Zero is licensed under MIT, while Gemma 3 12B 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 12B

Gemma

Open weights

Release Timeline

When each model was launched

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

Gemma 3 12B is 2 months newer than DeepSeek R1 Zero.

DeepSeek R1 Zero

Jan 20, 2025

1.2 years ago

Gemma 3 12B

Mar 12, 2025

1.1 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 40.9%)
Higher LiveCodeBench score (50.0% vs 24.6%)
Google
Larger context window (131,072 tokens)
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Zero
Google
Gemma 3 12B

FAQ

Common questions about DeepSeek R1 Zero vs Gemma 3 12B

DeepSeek R1 Zero significantly outperforms across most benchmarks. DeepSeek R1 Zero is made by DeepSeek and Gemma 3 12B is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek R1 Zero scores MATH-500: 95.9%, AIME 2024: 86.7%, GPQA: 73.3%, LiveCodeBench: 50.0%. Gemma 3 12B scores GSM8k: 94.4%, IFEval: 88.9%, DocVQA: 87.1%, BIG-Bench Hard: 85.7%, HumanEval: 85.4%.
DeepSeek R1 Zero supports an unknown number of tokens and Gemma 3 12B supports 131K 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 Zero is developed by DeepSeek and Gemma 3 12B is developed by Google.