Model Comparison

DeepSeek-R1 vs Gemma 2 27B

Comparing DeepSeek-R1 and Gemma 2 27B across benchmarks, pricing, and capabilities.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-R1 and Gemma 2 27B don'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

Cost data unavailable.

Lowest available price from all providers
Fri Apr 03 2026 • llm-stats.com
DeepSeek
DeepSeek-R1
Input tokens$0.55
Output tokens$2.19
Best providerDeepSeek
Google
Gemma 2 27B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

643.8B diff

DeepSeek-R1 has 643.8B more parameters than Gemma 2 27B, making it 2366.9% larger.

DeepSeek
DeepSeek-R1
671.0Bparameters
Google
Gemma 2 27B
27.2Bparameters
671.0B
DeepSeek-R1
27.2B
Gemma 2 27B

Context Window

Maximum input and output token capacity

Only DeepSeek-R1 specifies input context (131,072 tokens). Only DeepSeek-R1 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-R1
Input131,072 tokens
Output131,072 tokens
Google
Gemma 2 27B
Input- tokens
Output- tokens
Fri Apr 03 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-R1 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.

DeepSeek-R1

MIT

Open weights

Gemma 2 27B

Gemma

Open weights

Release Timeline

When each model was launched

DeepSeek-R1 was released on 2025-01-20, while Gemma 2 27B was released on 2024-06-27.

DeepSeek-R1 is 7 months newer than Gemma 2 27B.

DeepSeek-R1

Jan 20, 2025

1.2 years ago

6mo newer
Gemma 2 27B

Jun 27, 2024

1.8 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Larger context window (131,072 tokens)
Google

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-R1
Google
Gemma 2 27B

FAQ

Common questions about DeepSeek-R1 vs Gemma 2 27B

DeepSeek-R1 (DeepSeek) and Gemma 2 27B (Google) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
Gemma 2 27B scores ARC-E: 88.6%, HellaSwag: 86.4%, BoolQ: 84.8%, TriviaQA: 83.7%, Winogrande: 83.7%.
DeepSeek-R1 supports 131K tokens and Gemma 2 27B supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (MIT vs Gemma). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-R1 is developed by DeepSeek and Gemma 2 27B is developed by Google.