Model Comparison

DeepSeek VL2 vs Gemini 2.0 Flash-LiteWhich is better in 2026?

Gemini 2.0 Flash-Lite significantly outperforms across most benchmarks.

Verdict: DeepSeek VL2 vs Gemini 2.0 Flash-Lite — which is better?

DeepSeek VL2 (by DeepSeek) and Gemini 2.0 Flash-Lite (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.

DeepSeek VL2 outperforms in 0 benchmarks, while Gemini 2.0 Flash-Lite is better at 1 benchmark (MMMU). Gemini 2.0 Flash-Lite significantly outperforms across most benchmarks.

Gemini 2.0 Flash-Lite also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.

Choose DeepSeek VL2 if…

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

Choose Gemini 2.0 Flash-Lite if…

  • you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Feb 2025
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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek VL2 outperforms in 0 benchmarks, while Gemini 2.0 Flash-Lite is better at 1 benchmark (MMMU).

Gemini 2.0 Flash-Lite significantly outperforms across most benchmarks.

Tue Jun 09 2026 • llm-stats.com

Arena Performance

Human preference votes

Context Window

Maximum input and output token capacity

Gemini 2.0 Flash-Lite accepts 1,048,576 input tokens compared to DeepSeek VL2's 129,280 tokens. DeepSeek VL2 can generate longer responses up to 129,280 tokens, while Gemini 2.0 Flash-Lite is limited to 8,192 tokens.

DeepSeek
DeepSeek VL2
Input129,280 tokens
Output129,280 tokens
Google
Gemini 2.0 Flash-Lite
Input1,048,576 tokens
Output8,192 tokens
Tue Jun 09 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both DeepSeek VL2 and Gemini 2.0 Flash-Lite support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

DeepSeek VL2

Text
Images
Audio
Video

Gemini 2.0 Flash-Lite

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 is licensed under deepseek, while Gemini 2.0 Flash-Lite uses a proprietary license.

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

DeepSeek VL2

deepseek

Open weights

Gemini 2.0 Flash-Lite

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek VL2 was released on 2024-12-13, while Gemini 2.0 Flash-Lite was released on 2025-02-05.

Gemini 2.0 Flash-Lite is 2 months newer than DeepSeek VL2.

DeepSeek VL2

Dec 13, 2024

1.5 years ago

Gemini 2.0 Flash-Lite

Feb 5, 2025

1.3 years ago

1mo newer

Knowledge Cutoff

When training data ends

Gemini 2.0 Flash-Lite has a documented knowledge cutoff of 2024-06-01, while DeepSeek VL2's cutoff date is not specified.

We can confirm Gemini 2.0 Flash-Lite's training data extends to 2024-06-01, but cannot make a direct comparison without DeepSeek VL2's cutoff date.

DeepSeek VL2

—

Gemini 2.0 Flash-Lite

Jun 2024

Provider Availability

DeepSeek VL2 is available from Replicate. Gemini 2.0 Flash-Lite is available from Google.

DeepSeek VL2

replicate logo
Replicate

Gemini 2.0 Flash-Lite

google logo
Google
Input Price:Input: $0.07/1MOutput Price:Output: $0.30/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek
Has open weights
Google
Larger context window (1,048,576 tokens)
Higher MMMU score (68.0% vs 51.1%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2
Google
Gemini 2.0 Flash-Lite

FAQ

Common questions about DeepSeek VL2 vs Gemini 2.0 Flash-Lite.

Which is better, DeepSeek VL2 or Gemini 2.0 Flash-Lite?

Gemini 2.0 Flash-Lite significantly outperforms across most benchmarks. DeepSeek VL2 is made by DeepSeek and Gemini 2.0 Flash-Lite is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek VL2 compare to Gemini 2.0 Flash-Lite in benchmarks?

DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%. Gemini 2.0 Flash-Lite scores MATH: 86.8%, FACTS Grounding: 83.6%, Global-MMLU-Lite: 78.2%, MMLU-Pro: 71.6%, MMMU: 68.0%.

What are the context window sizes for DeepSeek VL2 and Gemini 2.0 Flash-Lite?

DeepSeek VL2 supports 129K tokens and Gemini 2.0 Flash-Lite supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek VL2 and Gemini 2.0 Flash-Lite?

Key differences include context window (129K vs 1.0M), licensing (deepseek vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek VL2 and Gemini 2.0 Flash-Lite?

DeepSeek VL2 is developed by DeepSeek and Gemini 2.0 Flash-Lite is developed by Google.

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