DeepSeek R1 Distill Qwen 1.5B vs Gemma 3 27B
Gemma 3 27B leads the LLM Stats Score 8.5 to -2.7.
DeepSeek · Google · Updated for 2026
Which is better?
Gemma 3 27B leads the overall LLM Stats Score 8.5 to -2.7, ranking #264 overall.
In the 2 individual benchmarks reported for both models, Gemma 3 27B wins 2; this is a narrower head-to-head signal than the composite indexes.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek R1 Distill Qwen 1.5B
- you are already invested in the DeepSeek ecosystem
Choose Gemma 3 27B
- overall performance matters — it scores 8.5 and ranks #264 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- you want the most recent training data — it shipped Mar 2025
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 Distill Qwen 1.5B · 27 for Gemma 3 27B
DeepSeek R1 Distill Qwen 1.5B outperforms in 0 benchmarks, while Gemma 3 27B is better at 2 benchmarks (GPQA, LiveCodeBench).
Gemma 3 27B significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
Gemma 3 27B has 25.2B more parameters than DeepSeek R1 Distill Qwen 1.5B, making it 1416.9% larger.
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).
Input capabilities
Documented input modalities across available providers
Gemma 3 27B supports multimodal inputs, whereas DeepSeek R1 Distill Qwen 1.5B does not.
Gemma 3 27B can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek R1 Distill Qwen 1.5B
Gemma 3 27B
License
Usage and distribution terms
DeepSeek R1 Distill Qwen 1.5B 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.
MIT
Open weights
Gemma
Open weights
Release Timeline
When each model was launched
DeepSeek R1 Distill Qwen 1.5B 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 Distill Qwen 1.5B.
Jan 20, 2025
1.6 years ago
Mar 12, 2025
1.5 years ago
1mo newerKnowledge 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 Distill Qwen 1.5B and Gemma 3 27B side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek R1 Distill Qwen 1.5B vs Gemma 3 27B.