Model Comparison

Gemma 2 9B vs DeepSeek-R1

Comparing Gemma 2 9B 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 9B 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
Tue Mar 31 2026 • llm-stats.com
Google
Gemma 2 9B
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

661.8B diff

DeepSeek-R1 has 661.8B more parameters than Gemma 2 9B, making it 7161.9% larger.

Google
Gemma 2 9B
9.2Bparameters
DeepSeek
DeepSeek-R1
671.0Bparameters
9.2B
Gemma 2 9B
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 9B
Input- tokens
Output- tokens
DeepSeek
DeepSeek-R1
Input131,072 tokens
Output131,072 tokens
Tue Mar 31 2026 • llm-stats.com

License

Usage and distribution terms

Gemma 2 9B 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 9B

Gemma

Open weights

DeepSeek-R1

MIT

Open weights

Release Timeline

When each model was launched

Gemma 2 9B was released on 2024-06-27, while DeepSeek-R1 was released on 2025-01-20.

DeepSeek-R1 is 7 months newer than Gemma 2 9B.

Gemma 2 9B

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

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Key Takeaways

Google
DeepSeek
Larger context window (131,072 tokens)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemma 2 9B
DeepSeek
DeepSeek-R1

FAQ

Common questions about Gemma 2 9B vs DeepSeek-R1

Gemma 2 9B (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 9B scores ARC-E: 88.0%, BoolQ: 84.2%, HellaSwag: 81.9%, PIQA: 81.7%, Winogrande: 80.6%.
Gemma 2 9B 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 9B is developed by Google and DeepSeek-R1 is developed by DeepSeek.