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DeepSeek-V2.5 vs Gemini 2.0 Flash Thinking

Comparing DeepSeek-V2.5 and Gemini 2.0 Flash Thinking across benchmarks, pricing, and capabilities.

DeepSeek · Google · Updated for 2026

Which is better?

DeepSeek-V2.5 and Gemini 2.0 Flash Thinking 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-V2.5

  • you need open weights you can self-host or fine-tune

Choose Gemini 2.0 Flash Thinking

  • you want the most recent training data — it shipped Jan 2025

At a glance

The differences that matter most.

DeepSeek-V2.5
DeepSeek
Gemini 2.0 Flash Thinking
Google
Benchmark wins
—
—
Input price
$0.14 / M
— / M
Output price
$0.28 / M
— / M
Context window
8,192
—
Released
May 2024
Jan 2025
License
deepseek
Proprietary

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V2.5 and Gemini 2.0 Flash Thinkingdon'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

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
Gemini 2.0 Flash Thinking
Input- tokens
Output- tokens
Tue Aug 25 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemini 2.0 Flash Thinking supports multimodal inputs, whereas DeepSeek-V2.5 does not.

Gemini 2.0 Flash Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V2.5

Text
Images
Audio
Video

Gemini 2.0 Flash Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V2.5 is licensed under deepseek, while Gemini 2.0 Flash Thinking uses a proprietary license.

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

DeepSeek-V2.5

deepseek

Open weights

Gemini 2.0 Flash Thinking

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V2.5 was released on 2024-05-08, while Gemini 2.0 Flash Thinking was released on 2025-01-21.

Gemini 2.0 Flash Thinking is 9 months newer than DeepSeek-V2.5.

DeepSeek-V2.5

May 8, 2024

2.3 years ago

Gemini 2.0 Flash Thinking

Jan 21, 2025

1.6 years ago

8mo newer

Knowledge Cutoff

When training data ends

Gemini 2.0 Flash Thinking has a documented knowledge cutoff of 2024-08-01, while DeepSeek-V2.5's cutoff date is not specified.

We can confirm Gemini 2.0 Flash Thinking's training data extends to 2024-08-01, but cannot make a direct comparison without DeepSeek-V2.5's cutoff date.

DeepSeek-V2.5

—

Gemini 2.0 Flash Thinking

Aug 2024

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek-V2.5 and Gemini 2.0 Flash Thinking side-by-side, then vote on the output you prefer.

DeepSeek-V2.5
✓ Preferred
Gemini 2.0 Flash Thinking
Open in Playground

FAQ

Common questions about DeepSeek-V2.5 vs Gemini 2.0 Flash Thinking.

Which is better, DeepSeek-V2.5 or Gemini 2.0 Flash Thinking?

DeepSeek-V2.5 (DeepSeek) and Gemini 2.0 Flash Thinking (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-V2.5 compare to Gemini 2.0 Flash Thinking in benchmarks?

DeepSeek-V2.5 scores GSM8k: 95.1%, MT-Bench: 90.2%, HumanEval: 89.0%, BBH: 84.3%, AlignBench: 80.4%. Gemini 2.0 Flash Thinking scores MMMU: 75.4%, GPQA: 74.2%, AIME 2024: 73.3%.

What are the context window sizes for DeepSeek-V2.5 and Gemini 2.0 Flash Thinking?

DeepSeek-V2.5 supports 8K tokens and Gemini 2.0 Flash Thinking 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 Gemini 2.0 Flash Thinking?

Key differences include multimodal support (no vs yes), licensing (deepseek vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V2.5 and Gemini 2.0 Flash Thinking?

DeepSeek-V2.5 is developed by DeepSeek and Gemini 2.0 Flash Thinking is developed by Google.

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