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DeepSeek-V4-Pro-0813 vs Gemma 2 27B

Comparing DeepSeek-V4-Pro-0813 and Gemma 2 27B across benchmarks, pricing, and capabilities.

DeepSeek · Google · Updated for 2026

Which is better?

DeepSeek-V4-Pro-0813 and Gemma 2 27B trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

Based on current benchmark, pricing, and model metadata for 2026.

Choose DeepSeek-V4-Pro-0813

  • you want the most recent training data — it shipped Aug 2026

Choose Gemma 2 27B

  • you are already invested in the Google ecosystem

At a glance

The differences that matter most.

DeepSeek-V4-Pro-0813
DeepSeek
Gemma 2 27B
Google
Benchmark wins
—
—
Input price
$0.43 / M
— / M
Output price
$0.87 / M
— / M
Context window
1,048,576
—
Released
Aug 2026
Jun 2024
License
MIT
Gemma

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V4-Pro-0813 and Gemma 2 27Bdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

1572.8B diff

DeepSeek-V4-Pro-0813 has 1572.8B more parameters than Gemma 2 27B, making it 5782.4% larger.

DeepSeek
DeepSeek-V4-Pro-0813
1.6Tparameters
Google
Gemma 2 27B
27.2Bparameters
1600.0B
DeepSeek-V4-Pro-0813
27.2B
Gemma 2 27B

Context Window

Maximum input and output token capacity

Only DeepSeek-V4-Pro-0813 specifies input context (1,048,576 tokens). Only DeepSeek-V4-Pro-0813 specifies output context (393,216 tokens).

DeepSeek
DeepSeek-V4-Pro-0813
Input1,048,576 tokens
Output393,216 tokens
Google
Gemma 2 27B
Input- tokens
Output- tokens
Mon Aug 24 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V4-Pro-0813 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-V4-Pro-0813

MIT

Open weights

Gemma 2 27B

Gemma

Open weights

Release Timeline

When each model was launched

DeepSeek-V4-Pro-0813 was released on 2026-08-13, while Gemma 2 27B was released on 2024-06-27.

DeepSeek-V4-Pro-0813 is 26 months newer than Gemma 2 27B.

DeepSeek-V4-Pro-0813

Aug 13, 2026

1 weeks ago

2.1yr newer
Gemma 2 27B

Jun 27, 2024

2.2 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→

Judge for yourself.

Run your own prompts against DeepSeek-V4-Pro-0813 and Gemma 2 27B side-by-side, then vote on the output you prefer.

DeepSeek-V4-Pro-0813
✓ Preferred
Gemma 2 27B
Open in Playground

FAQ

Common questions about DeepSeek-V4-Pro-0813 vs Gemma 2 27B.

Which is better, DeepSeek-V4-Pro-0813 or Gemma 2 27B?

DeepSeek-V4-Pro-0813 (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.

How does DeepSeek-V4-Pro-0813 compare to Gemma 2 27B in benchmarks?

DeepSeek-V4-Pro-0813 scores Terminal-Bench 2.1: 87.9%, CyberGym: 83.3%, Toolathlon: 74.1%, DSBench-FullStack: 71.1%, DSBench-Hard: 67.2%. Gemma 2 27B scores ARC-E: 88.6%, HellaSwag: 86.4%, BoolQ: 84.8%, TriviaQA: 83.7%, Winogrande: 83.7%.

What are the context window sizes for DeepSeek-V4-Pro-0813 and Gemma 2 27B?

DeepSeek-V4-Pro-0813 supports 1.0M 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.

What are the main differences between DeepSeek-V4-Pro-0813 and Gemma 2 27B?

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

Who makes DeepSeek-V4-Pro-0813 and Gemma 2 27B?

DeepSeek-V4-Pro-0813 is developed by DeepSeek and Gemma 2 27B is developed by Google.

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