Model Comparison

Gemini 1.5 Flash vs DeepSeek VL2 Tiny

Gemini 1.5 Flash significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

Gemini 1.5 Flash outperforms in 2 benchmarks (MathVista, MMMU), while DeepSeek VL2 Tiny is better at 0 benchmarks.

Gemini 1.5 Flash significantly outperforms across most benchmarks.

Sat May 30 2026 • llm-stats.com

Arena Performance

Human preference votes

Context Window

Maximum input and output token capacity

Only Gemini 1.5 Flash specifies input context (1,048,576 tokens). Only Gemini 1.5 Flash specifies output context (8,192 tokens).

Google
Gemini 1.5 Flash
Input1,048,576 tokens
Output8,192 tokens
DeepSeek
DeepSeek VL2 Tiny
Input- tokens
Output- tokens
Sat May 30 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Gemini 1.5 Flash and DeepSeek VL2 Tiny support multimodal inputs.

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

Gemini 1.5 Flash

Text
Images
Audio
Video

DeepSeek VL2 Tiny

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 1.5 Flash is licensed under a proprietary license, while DeepSeek VL2 Tiny uses deepseek.

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

Gemini 1.5 Flash

Proprietary

Closed source

DeepSeek VL2 Tiny

deepseek

Open weights

Release Timeline

When each model was launched

Gemini 1.5 Flash was released on 2024-05-01, while DeepSeek VL2 Tiny was released on 2024-12-13.

DeepSeek VL2 Tiny is 8 months newer than Gemini 1.5 Flash.

Gemini 1.5 Flash

May 1, 2024

2.1 years ago

DeepSeek VL2 Tiny

Dec 13, 2024

1.5 years ago

7mo newer

Knowledge Cutoff

When training data ends

Gemini 1.5 Flash has a documented knowledge cutoff of 2023-11-01, while DeepSeek VL2 Tiny's cutoff date is not specified.

We can confirm Gemini 1.5 Flash's training data extends to 2023-11-01, but cannot make a direct comparison without DeepSeek VL2 Tiny's cutoff date.

Gemini 1.5 Flash

Nov 2023

DeepSeek VL2 Tiny

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Outputs Comparison

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Key Takeaways

Google
Larger context window (1,048,576 tokens)
Higher MathVista score (65.8% vs 53.6%)
Higher MMMU score (62.3% vs 40.7%)
DeepSeek
Has open weights
GoogleGemini 1.5 Flash
DeepSeekDeepSeek VL2 Tiny
Compare in Playground

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini 1.5 Flash
DeepSeek
DeepSeek VL2 Tiny

FAQ

Common questions about Gemini 1.5 Flash vs DeepSeek VL2 Tiny.

Which is better, Gemini 1.5 Flash or DeepSeek VL2 Tiny?

Gemini 1.5 Flash significantly outperforms across most benchmarks. Gemini 1.5 Flash is made by Google and DeepSeek VL2 Tiny is made by DeepSeek. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Gemini 1.5 Flash compare to DeepSeek VL2 Tiny in benchmarks?

Gemini 1.5 Flash scores XSTest: 97.0%, HellaSwag: 86.5%, GSM8k: 86.2%, BIG-Bench Hard: 85.5%, MGSM: 82.6%. DeepSeek VL2 Tiny scores DocVQA: 88.9%, ChartQA: 81.0%, OCRBench: 80.9%, TextVQA: 80.7%, AI2D: 71.6%.

What are the context window sizes for Gemini 1.5 Flash and DeepSeek VL2 Tiny?

Gemini 1.5 Flash supports 1.0M tokens and DeepSeek VL2 Tiny 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 Gemini 1.5 Flash and DeepSeek VL2 Tiny?

Key differences include licensing (Proprietary vs deepseek). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 1.5 Flash and DeepSeek VL2 Tiny?

Gemini 1.5 Flash is developed by Google and DeepSeek VL2 Tiny is developed by DeepSeek.