DeepSeek R1 Distill Qwen 32B vs Gemma 3 27B
DeepSeek R1 Distill Qwen 32B leads the LLM Stats Score 13.1 to 8.3. Gemma 3 27B is 1.4x cheaper per token.
DeepSeek · Google · Updated for 2026
Which is better?
DeepSeek R1 Distill Qwen 32B leads the overall LLM Stats Score 13.1 to 8.3, ranking #248 overall.
In the 2 individual benchmarks reported for both models, DeepSeek R1 Distill Qwen 32B wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, Gemma 3 27B is roughly 1.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemma 3 27B also accepts a larger context window (131,072 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek R1 Distill Qwen 32B
- overall performance matters — it scores 13.1 and ranks #248 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
Choose Gemma 3 27B
- cost matters — it's about 1.4x cheaper per token
- you process long inputs — it offers a 131,072 token context window
- 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 32B · 27 for Gemma 3 27B
DeepSeek R1 Distill Qwen 32B outperforms in 2 benchmarks (GPQA, LiveCodeBench), while Gemma 3 27B is better at 0 benchmarks.
DeepSeek R1 Distill Qwen 32B significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek R1 Distill Qwen 32B ($0.12/1M tokens) is 1.5x more expensive than Gemma 3 27B ($0.08/1M tokens).
For output processing, DeepSeek R1 Distill Qwen 32B ($0.18/1M tokens) is 1.1x more expensive than Gemma 3 27B ($0.16/1M tokens).
In conclusion, DeepSeek R1 Distill Qwen 32B is more expensive than Gemma 3 27B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek R1 Distill Qwen 32B has 5.8B more parameters than Gemma 3 27B, making it 21.5% larger.
Context Window
Maximum input and output token capacity
Gemma 3 27B accepts 131,072 input tokens compared to DeepSeek R1 Distill Qwen 32B's 128,000 tokens. Gemma 3 27B can generate longer responses up to 131,072 tokens, while DeepSeek R1 Distill Qwen 32B is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Gemma 3 27B supports multimodal inputs, whereas DeepSeek R1 Distill Qwen 32B 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 32B
Gemma 3 27B
License
Usage and distribution terms
DeepSeek R1 Distill Qwen 32B 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 32B 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 32B.
Jan 20, 2025
1.7 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.
Provider Availability
DeepSeek R1 Distill Qwen 32B is available from DeepInfra. Gemma 3 27B is available from DeepInfra, Novita.
DeepSeek R1 Distill Qwen 32B
Gemma 3 27B
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek R1 Distill Qwen 32B and Gemma 3 27B side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek R1 Distill Qwen 32B vs Gemma 3 27B.