Model Comparison

Gemma 2 27B vs DeepSeek-R1

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

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Gemma 2 27B and DeepSeek-R1 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
Sat Apr 04 2026 • llm-stats.com
Google
Gemma 2 27B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
DeepSeek
DeepSeek-R1
Input tokens$0.55
Output tokens$2.19
Best providerDeepSeek
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.

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

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).

Google
Gemma 2 27B
Input- tokens
Output- tokens
DeepSeek
DeepSeek-R1
Input131,072 tokens
Output131,072 tokens
Sat Apr 04 2026 • llm-stats.com

License

Usage and distribution terms

Gemma 2 27B is licensed under Gemma, while DeepSeek-R1 uses MIT.

License differences may affect how you can use these models in commercial or open-source projects.

Gemma 2 27B

Gemma

Open weights

DeepSeek-R1

MIT

Open weights

Release Timeline

When each model was launched

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

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

Gemma 2 27B

Jun 27, 2024

1.8 years ago

DeepSeek-R1

Jan 20, 2025

1.2 years ago

6mo newer

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

Google
DeepSeek
Larger context window (131,072 tokens)

Detailed Comparison

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

FAQ

Common questions about Gemma 2 27B vs DeepSeek-R1

Gemma 2 27B (Google) and DeepSeek-R1 (DeepSeek) 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%.
Gemma 2 27B supports an unknown number of tokens and DeepSeek-R1 supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (Gemma vs MIT). See the full comparison above for benchmark-by-benchmark results.
Gemma 2 27B is developed by Google and DeepSeek-R1 is developed by DeepSeek.