Model Comparison

DeepSeek VL2 Small vs Gemini 2.0 Flash-Lite

Gemini 2.0 Flash-Lite significantly outperforms across most benchmarks.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek VL2 Small 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.

Fri May 01 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
Fri May 01 2026 • llm-stats.com
DeepSeek
DeepSeek VL2 Small
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Google
Gemini 2.0 Flash-Lite
Input tokens$0.07
Output tokens$0.30
Best providerGoogle
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Only Gemini 2.0 Flash-Lite specifies input context (1,048,576 tokens). Only Gemini 2.0 Flash-Lite specifies output context (8,192 tokens).

DeepSeek
DeepSeek VL2 Small
Input- tokens
Output- tokens
Google
Gemini 2.0 Flash-Lite
Input1,048,576 tokens
Output8,192 tokens
Fri May 01 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both DeepSeek VL2 Small 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 Small

Text
Images
Audio
Video

Gemini 2.0 Flash-Lite

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 Small 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 Small

deepseek

Open weights

Gemini 2.0 Flash-Lite

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek VL2 Small 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 Small.

DeepSeek VL2 Small

Dec 13, 2024

1.4 years ago

Gemini 2.0 Flash-Lite

Feb 5, 2025

1.2 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 Small'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 Small's cutoff date.

DeepSeek VL2 Small

—

Gemini 2.0 Flash-Lite

Jun 2024

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Has open weights
Google
Larger context window (1,048,576 tokens)
Higher MMMU score (68.0% vs 48.0%)

Detailed Comparison

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

FAQ

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

Gemini 2.0 Flash-Lite significantly outperforms across most benchmarks. DeepSeek VL2 Small 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.
DeepSeek VL2 Small scores DocVQA: 92.3%, ChartQA: 84.5%, OCRBench: 83.4%, TextVQA: 83.4%, MMBench: 80.3%. 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%.
DeepSeek VL2 Small supports an unknown number of 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.
Key differences include licensing (deepseek vs Proprietary). See the full comparison above for benchmark-by-benchmark results.
DeepSeek VL2 Small is developed by DeepSeek and Gemini 2.0 Flash-Lite is developed by Google.