Model Comparison

DeepSeek-V3 vs Gemini 2.0 Flash

Gemini 2.0 Flash shows notably better performance in the majority of benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

DeepSeek-V3 outperforms in 1 benchmarks (LiveCodeBench), while Gemini 2.0 Flash is better at 2 benchmarks (GPQA, MMLU-Pro).

Gemini 2.0 Flash shows notably better performance in the majority of benchmarks.

Thu Apr 02 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Thu Apr 02 2026 • llm-stats.com
DeepSeek
DeepSeek-V3
Input tokens$0.27
Output tokens$1.10
Best providerDeepSeek
Google
Gemini 2.0 Flash
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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Context Window

Maximum input and output token capacity

Only DeepSeek-V3 specifies input context (131,072 tokens). Only DeepSeek-V3 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
Google
Gemini 2.0 Flash
Input- tokens
Output- tokens
Thu Apr 02 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemini 2.0 Flash supports multimodal inputs, whereas DeepSeek-V3 does not.

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

DeepSeek-V3

Text
Images
Audio
Video

Gemini 2.0 Flash

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while Gemini 2.0 Flash uses a proprietary license.

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

DeepSeek-V3

MIT + Model License (Commercial use allowed)

Open weights

Gemini 2.0 Flash

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while Gemini 2.0 Flash was released on 2024-12-01.

DeepSeek-V3 is 1 month newer than Gemini 2.0 Flash.

DeepSeek-V3

Dec 25, 2024

1.3 years ago

3w newer
Gemini 2.0 Flash

Dec 1, 2024

1.3 years ago

Knowledge Cutoff

When training data ends

Gemini 2.0 Flash has a documented knowledge cutoff of 2024-08-01, while DeepSeek-V3's cutoff date is not specified.

We can confirm Gemini 2.0 Flash's training data extends to 2024-08-01, but cannot make a direct comparison without DeepSeek-V3's cutoff date.

DeepSeek-V3

—

Gemini 2.0 Flash

Aug 2024

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (131,072 tokens)
Has open weights
Higher LiveCodeBench score (37.6% vs 35.1%)
Google
Supports multimodal inputs
Higher GPQA score (62.1% vs 59.1%)
Higher MMLU-Pro score (76.4% vs 75.9%)
DeepSeekDeepSeek-V3
GoogleGemini 2.0 Flash
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Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3
Google
Gemini 2.0 Flash

FAQ

Common questions about DeepSeek-V3 vs Gemini 2.0 Flash

Gemini 2.0 Flash shows notably better performance in the majority of benchmarks. DeepSeek-V3 is made by DeepSeek and Gemini 2.0 Flash is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. Gemini 2.0 Flash scores Natural2Code: 92.9%, MATH: 89.7%, FACTS Grounding: 83.6%, MMLU-Pro: 76.4%, EgoSchema: 71.5%.
DeepSeek-V3 supports 131K tokens and Gemini 2.0 Flash 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 multimodal support (no vs yes), licensing (MIT + Model License (Commercial use allowed) vs Proprietary). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3 is developed by DeepSeek and Gemini 2.0 Flash is developed by Google.