Model Comparison

Gemini 1.5 Flash vs DeepSeek R1 Zero

DeepSeek R1 Zero significantly outperforms across most benchmarks.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

Gemini 1.5 Flash outperforms in 0 benchmarks, while DeepSeek R1 Zero is better at 1 benchmark (GPQA).

DeepSeek R1 Zero significantly outperforms across most benchmarks.

Tue May 12 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 R1 Zero
Input- tokens
Output- tokens
Tue May 12 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemini 1.5 Flash supports multimodal inputs, whereas DeepSeek R1 Zero does not.

Gemini 1.5 Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemini 1.5 Flash

Text
Images
Audio
Video

DeepSeek R1 Zero

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 1.5 Flash is licensed under a proprietary license, while DeepSeek R1 Zero uses MIT.

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

Gemini 1.5 Flash

Proprietary

Closed source

DeepSeek R1 Zero

MIT

Open weights

Release Timeline

When each model was launched

Gemini 1.5 Flash was released on 2024-05-01, while DeepSeek R1 Zero was released on 2025-01-20.

DeepSeek R1 Zero is 9 months newer than Gemini 1.5 Flash.

Gemini 1.5 Flash

May 1, 2024

2.0 years ago

DeepSeek R1 Zero

Jan 20, 2025

1.3 years ago

8mo newer

Knowledge Cutoff

When training data ends

Gemini 1.5 Flash has a documented knowledge cutoff of 2023-11-01, while DeepSeek R1 Zero'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 R1 Zero's cutoff date.

Gemini 1.5 Flash

Nov 2023

DeepSeek R1 Zero

—

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Google
Larger context window (1,048,576 tokens)
Supports multimodal inputs
DeepSeek
Has open weights
Higher GPQA score (73.3% vs 51.0%)
GoogleGemini 1.5 Flash
DeepSeekDeepSeek R1 Zero
Compare in Playground

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini 1.5 Flash
DeepSeek
DeepSeek R1 Zero

FAQ

Common questions about Gemini 1.5 Flash vs DeepSeek R1 Zero.

Which is better, Gemini 1.5 Flash or DeepSeek R1 Zero?

DeepSeek R1 Zero significantly outperforms across most benchmarks. Gemini 1.5 Flash is made by Google and DeepSeek R1 Zero 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 R1 Zero 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 R1 Zero scores MATH-500: 95.9%, AIME 2024: 86.7%, GPQA: 73.3%, LiveCodeBench: 50.0%.

What are the context window sizes for Gemini 1.5 Flash and DeepSeek R1 Zero?

Gemini 1.5 Flash supports 1.0M tokens and DeepSeek R1 Zero 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 R1 Zero?

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

Who makes Gemini 1.5 Flash and DeepSeek R1 Zero?

Gemini 1.5 Flash is developed by Google and DeepSeek R1 Zero is developed by DeepSeek.