Model Comparison

DeepSeek R1 Distill Qwen 1.5B vs Gemma 3n E2B Instructed

DeepSeek R1 Distill Qwen 1.5B significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DeepSeek R1 Distill Qwen 1.5B outperforms in 2 benchmarks (GPQA, LiveCodeBench), while Gemma 3n E2B Instructed is better at 0 benchmarks.

DeepSeek R1 Distill Qwen 1.5B significantly outperforms across most benchmarks.

Wed Apr 22 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
Wed Apr 22 2026 • llm-stats.com
DeepSeek
DeepSeek R1 Distill Qwen 1.5B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Google
Gemma 3n E2B Instructed
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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Model Size

Parameter count comparison

6.2B diff

Gemma 3n E2B Instructed has 6.2B more parameters than DeepSeek R1 Distill Qwen 1.5B, making it 349.4% larger.

DeepSeek
DeepSeek R1 Distill Qwen 1.5B
1.8Bparameters
Google
Gemma 3n E2B Instructed
8.0Bparameters
1.8B
DeepSeek R1 Distill Qwen 1.5B
8.0B
Gemma 3n E2B Instructed

Input Capabilities

Supported data types and modalities

Gemma 3n E2B Instructed supports multimodal inputs, whereas DeepSeek R1 Distill Qwen 1.5B does not.

Gemma 3n E2B Instructed can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek R1 Distill Qwen 1.5B

Text
Images
Audio
Video

Gemma 3n E2B Instructed

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek R1 Distill Qwen 1.5B is licensed under MIT, while Gemma 3n E2B Instructed uses a proprietary license.

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

DeepSeek R1 Distill Qwen 1.5B

MIT

Open weights

Gemma 3n E2B Instructed

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek R1 Distill Qwen 1.5B was released on 2025-01-20, while Gemma 3n E2B Instructed was released on 2025-06-26.

Gemma 3n E2B Instructed is 5 months newer than DeepSeek R1 Distill Qwen 1.5B.

DeepSeek R1 Distill Qwen 1.5B

Jan 20, 2025

1.3 years ago

Gemma 3n E2B Instructed

Jun 26, 2025

10 months ago

5mo newer

Knowledge Cutoff

When training data ends

Gemma 3n E2B Instructed has a documented knowledge cutoff of 2024-06-01, while DeepSeek R1 Distill Qwen 1.5B's cutoff date is not specified.

We can confirm Gemma 3n E2B Instructed's training data extends to 2024-06-01, but cannot make a direct comparison without DeepSeek R1 Distill Qwen 1.5B's cutoff date.

DeepSeek R1 Distill Qwen 1.5B

—

Gemma 3n E2B Instructed

Jun 2024

Outputs Comparison

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Key Takeaways

DeepSeek
Has open weights
Higher GPQA score (33.8% vs 24.8%)
Higher LiveCodeBench score (16.9% vs 13.2%)
Google
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Distill Qwen 1.5B
Google
Gemma 3n E2B Instructed

FAQ

Common questions about DeepSeek R1 Distill Qwen 1.5B vs Gemma 3n E2B Instructed

DeepSeek R1 Distill Qwen 1.5B significantly outperforms across most benchmarks. DeepSeek R1 Distill Qwen 1.5B is made by DeepSeek and Gemma 3n E2B Instructed is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek R1 Distill Qwen 1.5B scores MATH-500: 83.9%, AIME 2024: 52.7%, GPQA: 33.8%, LiveCodeBench: 16.9%. Gemma 3n E2B Instructed scores HumanEval: 66.5%, MMLU: 60.1%, Global-MMLU-Lite: 59.0%, MBPP: 56.6%, Global-MMLU: 55.1%.
Key differences include multimodal support (no vs yes), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.
DeepSeek R1 Distill Qwen 1.5B is developed by DeepSeek and Gemma 3n E2B Instructed is developed by Google.