Model Comparison

DeepSeek-R1-0528 vs Gemma 2 9BWhich is better in 2026?

Comparing DeepSeek-R1-0528 and Gemma 2 9B across benchmarks, pricing, and capabilities.

Verdict: DeepSeek-R1-0528 vs Gemma 2 9B — which is better?

DeepSeek-R1-0528 (by DeepSeek) and Gemma 2 9B (by Google) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

Choose DeepSeek-R1-0528 if…

  • you want the most recent training data — it shipped May 2025

Choose Gemma 2 9B if…

  • you are already invested in the Google ecosystem
Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-R1-0528 and Gemma 2 9Bdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Model Size

Parameter count comparison

661.8B diff

DeepSeek-R1-0528 has 661.8B more parameters than Gemma 2 9B, making it 7161.9% larger.

DeepSeek
DeepSeek-R1-0528
671.0Bparameters
Google
Gemma 2 9B
9.2Bparameters
671.0B
DeepSeek-R1-0528
9.2B
Gemma 2 9B

Context Window

Maximum input and output token capacity

Only DeepSeek-R1-0528 specifies input context (131,072 tokens). Only DeepSeek-R1-0528 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-R1-0528
Input131,072 tokens
Output131,072 tokens
Google
Gemma 2 9B
Input- tokens
Output- tokens
Mon Jun 22 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-R1-0528 is licensed under MIT, while Gemma 2 9B uses Gemma.

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

DeepSeek-R1-0528

MIT

Open weights

Gemma 2 9B

Gemma

Open weights

Release Timeline

When each model was launched

DeepSeek-R1-0528 was released on 2025-05-28, while Gemma 2 9B was released on 2024-06-27.

DeepSeek-R1-0528 is 11 months newer than Gemma 2 9B.

DeepSeek-R1-0528

May 28, 2025

1.1 years ago

11mo newer
Gemma 2 9B

Jun 27, 2024

2.0 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

No standout differentiators in the data we have for this pair.

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-R1-0528
Google
Gemma 2 9B

FAQ

Common questions about DeepSeek-R1-0528 vs Gemma 2 9B.

Which is better, DeepSeek-R1-0528 or Gemma 2 9B?

DeepSeek-R1-0528 (DeepSeek) and Gemma 2 9B (Google) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DeepSeek-R1-0528 compare to Gemma 2 9B in benchmarks?

DeepSeek-R1-0528 scores MMLU-Redux: 93.4%, SimpleQA: 92.3%, AIME 2024: 91.4%, AIME 2025: 87.5%, MMLU-Pro: 85.0%. Gemma 2 9B scores ARC-E: 88.0%, BoolQ: 84.2%, HellaSwag: 81.9%, PIQA: 81.7%, Winogrande: 80.6%.

What are the context window sizes for DeepSeek-R1-0528 and Gemma 2 9B?

DeepSeek-R1-0528 supports 131K tokens and Gemma 2 9B supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-R1-0528 and Gemma 2 9B?

Key differences include licensing (MIT vs Gemma). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-R1-0528 and Gemma 2 9B?

DeepSeek-R1-0528 is developed by DeepSeek and Gemma 2 9B is developed by Google.

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