Model Comparison
DeepSeek-R1 vs Gemma 3n E4B InstructedWhich is better in 2026?
Comparing DeepSeek-R1 and Gemma 3n E4B Instructed across benchmarks, pricing, and capabilities.
Verdict: DeepSeek-R1 vs Gemma 3n E4B Instructed — which is better?
DeepSeek-R1 (by DeepSeek) and Gemma 3n E4B Instructed (by Google) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
On price, DeepSeek-R1 is roughly 26.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-R1 also accepts a larger context window (131,072 input tokens), making it the stronger choice for long documents and large codebases.
Choose DeepSeek-R1 if…
- cost matters — it's about 26.0x cheaper per token
- you process long inputs — it offers a 131,072 token context window
- you need open weights you can self-host or fine-tune
Choose Gemma 3n E4B Instructed if…
- you want the most recent training data — it shipped Jun 2025
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-R1 and Gemma 3n E4B Instructeddon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-R1 ($0.55/1M tokens) is 36.4x cheaper than Gemma 3n E4B Instructed ($20.00/1M tokens).
For output processing, DeepSeek-R1 ($2.19/1M tokens) is 18.3x cheaper than Gemma 3n E4B Instructed ($40.00/1M tokens).
In conclusion, Gemma 3n E4B Instructed is more expensive than DeepSeek-R1.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-R1 has 663.0B more parameters than Gemma 3n E4B Instructed, making it 8287.5% larger.
Context Window
Maximum input and output token capacity
DeepSeek-R1 accepts 131,072 input tokens compared to Gemma 3n E4B Instructed's 32,000 tokens. DeepSeek-R1 can generate longer responses up to 131,072 tokens, while Gemma 3n E4B Instructed is limited to 32,000 tokens.
Input Capabilities
Supported data types and modalities
Gemma 3n E4B Instructed supports multimodal inputs, whereas DeepSeek-R1 does not.
Gemma 3n E4B Instructed can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-R1
Gemma 3n E4B Instructed
License
Usage and distribution terms
DeepSeek-R1 is licensed under MIT, while Gemma 3n E4B Instructed uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-R1 was released on 2025-01-20, while Gemma 3n E4B Instructed was released on 2025-06-26.
Gemma 3n E4B Instructed is 5 months newer than DeepSeek-R1.
Jan 20, 2025
1.5 years ago
Jun 26, 2025
1.0 years ago
5mo newerKnowledge Cutoff
When training data ends
Gemma 3n E4B Instructed has a documented knowledge cutoff of 2024-06-01, while DeepSeek-R1's cutoff date is not specified.
We can confirm Gemma 3n E4B Instructed's training data extends to 2024-06-01, but cannot make a direct comparison without DeepSeek-R1's cutoff date.
—
Jun 2024
Provider Availability
DeepSeek-R1 is available from DeepSeek, DeepInfra, Together, Fireworks. Gemma 3n E4B Instructed is available from Together.
DeepSeek-R1
Gemma 3n E4B Instructed
Outputs Comparison
Key Takeaways
DeepSeek-R1
View detailsDeepSeek
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-R1 and Gemma 3n E4B Instructed side-by-side, then vote on the output you prefer.
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FAQ
Common questions about DeepSeek-R1 vs Gemma 3n E4B Instructed.