Model Comparison

DeepSeek-V3.2-Exp vs Gemma 2 9B

Comparing DeepSeek-V3.2-Exp and Gemma 2 9B across benchmarks, pricing, and capabilities.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V3.2-Exp and Gemma 2 9B don'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

675.8B diff

DeepSeek-V3.2-Exp has 675.8B more parameters than Gemma 2 9B, making it 7313.4% larger.

DeepSeek
DeepSeek-V3.2-Exp
685.0Bparameters
Google
Gemma 2 9B
9.2Bparameters
685.0B
DeepSeek-V3.2-Exp
9.2B
Gemma 2 9B

Context Window

Maximum input and output token capacity

Only DeepSeek-V3.2-Exp specifies input context (163,840 tokens). Only DeepSeek-V3.2-Exp specifies output context (65,536 tokens).

DeepSeek
DeepSeek-V3.2-Exp
Input163,840 tokens
Output65,536 tokens
Google
Gemma 2 9B
Input- tokens
Output- tokens
Tue May 12 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3.2-Exp 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-V3.2-Exp

MIT

Open weights

Gemma 2 9B

Gemma

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2-Exp was released on 2025-09-29, while Gemma 2 9B was released on 2024-06-27.

DeepSeek-V3.2-Exp is 15 months newer than Gemma 2 9B.

DeepSeek-V3.2-Exp

Sep 29, 2025

7 months ago

1.3yr newer
Gemma 2 9B

Jun 27, 2024

1.9 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 (163,840 tokens)
Google

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

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2-Exp
Google
Gemma 2 9B

FAQ

Common questions about DeepSeek-V3.2-Exp vs Gemma 2 9B.

Which is better, DeepSeek-V3.2-Exp or Gemma 2 9B?

DeepSeek-V3.2-Exp (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-V3.2-Exp compare to Gemma 2 9B in benchmarks?

DeepSeek-V3.2-Exp scores SimpleQA: 97.1%, AIME 2025: 89.3%, MMLU-Pro: 85.0%, HMMT 2025: 83.6%, GPQA: 79.9%. 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-V3.2-Exp and Gemma 2 9B?

DeepSeek-V3.2-Exp supports 164K 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-V3.2-Exp and Gemma 2 9B?

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

Who makes DeepSeek-V3.2-Exp and Gemma 2 9B?

DeepSeek-V3.2-Exp is developed by DeepSeek and Gemma 2 9B is developed by Google.