Model Comparison

DeepSeek-V3.2-Exp vs Gemma 2 27B

Comparing DeepSeek-V3.2-Exp and Gemma 2 27B across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V3.2-Exp and Gemma 2 27B 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
Wed Apr 29 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2-Exp
Input tokens$0.27
Output tokens$0.41
Best providerNovita
Google
Gemma 2 27B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

657.8B diff

DeepSeek-V3.2-Exp has 657.8B more parameters than Gemma 2 27B, making it 2418.4% larger.

DeepSeek
DeepSeek-V3.2-Exp
685.0Bparameters
Google
Gemma 2 27B
27.2Bparameters
685.0B
DeepSeek-V3.2-Exp
27.2B
Gemma 2 27B

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 27B
Input- tokens
Output- tokens
Wed Apr 29 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3.2-Exp is licensed under MIT, while Gemma 2 27B 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 27B

Gemma

Open weights

Release Timeline

When each model was launched

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

DeepSeek-V3.2-Exp is 15 months newer than Gemma 2 27B.

DeepSeek-V3.2-Exp

Sep 29, 2025

7 months ago

1.3yr newer
Gemma 2 27B

Jun 27, 2024

1.8 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

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2-Exp
Google
Gemma 2 27B

FAQ

Common questions about DeepSeek-V3.2-Exp vs Gemma 2 27B

DeepSeek-V3.2-Exp (DeepSeek) and Gemma 2 27B (Google) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
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 27B scores ARC-E: 88.6%, HellaSwag: 86.4%, BoolQ: 84.8%, TriviaQA: 83.7%, Winogrande: 83.7%.
DeepSeek-V3.2-Exp supports 164K tokens and Gemma 2 27B supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (MIT vs Gemma). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3.2-Exp is developed by DeepSeek and Gemma 2 27B is developed by Google.