DeepSeek R1 Zero vs Gemma 2 27B
DeepSeek R1 Zero leads the LLM Stats Score 16.0 to -0.7.
DeepSeek · Google · Updated for 2026
Which is better?
DeepSeek R1 Zero leads the overall LLM Stats Score 16.0 to -0.7, ranking #225 overall.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek R1 Zero
- overall performance matters — it scores 16.0 and ranks #225 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you want the most recent training data — it shipped Jan 2025
Choose Gemma 2 27B
- you are already invested in the Google ecosystem
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
4 reported for DeepSeek R1 Zero · 16 for Gemma 2 27B
DeepSeek R1 Zero and Gemma 2 27Bdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
DeepSeek R1 Zero has 643.8B more parameters than Gemma 2 27B, making it 2366.9% larger.
License
Usage and distribution terms
DeepSeek R1 Zero is licensed under MIT, while Gemma 2 27B uses Gemma.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Gemma
Open weights
Release Timeline
When each model was launched
DeepSeek R1 Zero was released on 2025-01-20, while Gemma 2 27B was released on 2024-06-27.
DeepSeek R1 Zero is 7 months newer than Gemma 2 27B.
Jan 20, 2025
1.6 years ago
6mo newerJun 27, 2024
2.2 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek R1 Zero and Gemma 2 27B side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek R1 Zero vs Gemma 2 27B.