Model Comparison

DeepSeek-V2.5 vs Gemma 2 9B

DeepSeek-V2.5 significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

DeepSeek-V2.5 outperforms in 4 benchmarks (GSM8k, HumanEval, MATH, MMLU), while Gemma 2 9B is better at 0 benchmarks.

DeepSeek-V2.5 significantly outperforms across most benchmarks.

Sat May 09 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

226.8B diff

DeepSeek-V2.5 has 226.8B more parameters than Gemma 2 9B, making it 2454.1% larger.

DeepSeek
DeepSeek-V2.5
236.0Bparameters
Google
Gemma 2 9B
9.2Bparameters
236.0B
DeepSeek-V2.5
9.2B
Gemma 2 9B

Context Window

Maximum input and output token capacity

Only DeepSeek-V2.5 specifies input context (8,192 tokens). Only DeepSeek-V2.5 specifies output context (8,192 tokens).

DeepSeek
DeepSeek-V2.5
Input8,192 tokens
Output8,192 tokens
Google
Gemma 2 9B
Input- tokens
Output- tokens
Sat May 09 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V2.5 is licensed under deepseek, while Gemma 2 9B uses Gemma.

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

DeepSeek-V2.5

deepseek

Open weights

Gemma 2 9B

Gemma

Open weights

Release Timeline

When each model was launched

DeepSeek-V2.5 was released on 2024-05-08, while Gemma 2 9B was released on 2024-06-27.

Gemma 2 9B is 2 months newer than DeepSeek-V2.5.

DeepSeek-V2.5

May 8, 2024

2.0 years ago

Gemma 2 9B

Jun 27, 2024

1.9 years ago

1mo 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

DeepSeek
Larger context window (8,192 tokens)
Higher GSM8k score (95.1% vs 68.6%)
Higher HumanEval score (89.0% vs 40.2%)
Higher MATH score (74.7% vs 36.6%)
Higher MMLU score (80.4% vs 71.3%)
Google

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

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V2.5
Google
Gemma 2 9B

FAQ

Common questions about DeepSeek-V2.5 vs Gemma 2 9B.

Which is better, DeepSeek-V2.5 or Gemma 2 9B?

DeepSeek-V2.5 significantly outperforms across most benchmarks. DeepSeek-V2.5 is made by DeepSeek and Gemma 2 9B is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek-V2.5 compare to Gemma 2 9B in benchmarks?

DeepSeek-V2.5 scores GSM8k: 95.1%, MT-Bench: 90.2%, HumanEval: 89.0%, BBH: 84.3%, AlignBench: 80.4%. 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-V2.5 and Gemma 2 9B?

DeepSeek-V2.5 supports 8K 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-V2.5 and Gemma 2 9B?

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

Who makes DeepSeek-V2.5 and Gemma 2 9B?

DeepSeek-V2.5 is developed by DeepSeek and Gemma 2 9B is developed by Google.