Model Comparison

DeepSeek-V4-Flash-0731 vs Gemma 2 27BWhich is better in 2026?

Comparing DeepSeek-V4-Flash-0731 and Gemma 2 27B across benchmarks, pricing, and capabilities.

Verdict: DeepSeek-V4-Flash-0731 vs Gemma 2 27B — which is better?

DeepSeek-V4-Flash-0731 (by DeepSeek) and Gemma 2 27B (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-V4-Flash-0731 if…

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

Choose Gemma 2 27B if…

  • you are already invested in the Google ecosystem

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V4-Flash-0731 and Gemma 2 27Bdon'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

276.8B diff

DeepSeek-V4-Flash-0731 has 276.8B more parameters than Gemma 2 27B, making it 1017.6% larger.

DeepSeek
DeepSeek-V4-Flash-0731
304.0Bparameters
Google
Gemma 2 27B
27.2Bparameters
304.0B
DeepSeek-V4-Flash-0731
27.2B
Gemma 2 27B

Context Window

Maximum input and output token capacity

Only DeepSeek-V4-Flash-0731 specifies input context (1,048,576 tokens). Only DeepSeek-V4-Flash-0731 specifies output context (65,536 tokens).

DeepSeek
DeepSeek-V4-Flash-0731
Input1,048,576 tokens
Output65,536 tokens
Google
Gemma 2 27B
Input- tokens
Output- tokens
Mon Aug 03 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V4-Flash-0731 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-Flash-0731

MIT

Open weights

Gemma 2 27B

Gemma

Open weights

Release Timeline

When each model was launched

DeepSeek-V4-Flash-0731 was released on 2026-07-31, while Gemma 2 27B was released on 2024-06-27.

DeepSeek-V4-Flash-0731 is 25 months newer than Gemma 2 27B.

DeepSeek-V4-Flash-0731

Jul 31, 2026

3 days ago

2.1yr newer
Gemma 2 27B

Jun 27, 2024

2.1 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 (1,048,576 tokens)
Google

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

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against DeepSeek-V4-Flash-0731 and Gemma 2 27B side-by-side, then vote on the output you prefer.

DeepSeek-V4-Flash-0731
✓ Preferred
Gemma 2 27B
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V4-Flash-0731
Google
Gemma 2 27B

FAQ

Common questions about DeepSeek-V4-Flash-0731 vs Gemma 2 27B.

Which is better, DeepSeek-V4-Flash-0731 or Gemma 2 27B?

DeepSeek-V4-Flash-0731 (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-Flash-0731 compare to Gemma 2 27B in benchmarks?

DeepSeek-V4-Flash-0731 scores Terminal-Bench 2.1: 82.7%, CyberGym: 76.7%, Toolathlon: 70.3%, DSBench-FullStack: 68.7%, DSBench-Hard: 59.6%. 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-Flash-0731 and Gemma 2 27B?

DeepSeek-V4-Flash-0731 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-Flash-0731 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-Flash-0731 and Gemma 2 27B?

DeepSeek-V4-Flash-0731 is developed by DeepSeek and Gemma 2 27B is developed by Google.

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