Model Comparison

DeepSeek VL2 vs Gemini 3.5 Flash-LiteWhich is better in 2026?

Comparing DeepSeek VL2 and Gemini 3.5 Flash-Lite across benchmarks, pricing, and capabilities.

Verdict: DeepSeek VL2 vs Gemini 3.5 Flash-Lite — which is better?

DeepSeek VL2 (by DeepSeek) and Gemini 3.5 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.

Gemini 3.5 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 3.5 Flash-Lite if…

  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Jul 2026

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek VL2 and Gemini 3.5 Flash-Litedon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Context Window

Maximum input and output token capacity

Gemini 3.5 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 3.5 Flash-Lite is limited to 65,536 tokens.

DeepSeek
DeepSeek VL2
Input129,280 tokens
Output129,280 tokens
Google
Gemini 3.5 Flash-Lite
Input1,048,576 tokens
Output65,536 tokens
Sat Jul 25 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both DeepSeek VL2 and Gemini 3.5 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 3.5 Flash-Lite

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 is licensed under deepseek, while Gemini 3.5 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 3.5 Flash-Lite

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek VL2 was released on 2024-12-13, while Gemini 3.5 Flash-Lite was released on 2026-07-21.

Gemini 3.5 Flash-Lite is 20 months newer than DeepSeek VL2.

DeepSeek VL2

Dec 13, 2024

1.6 years ago

Gemini 3.5 Flash-Lite

Jul 21, 2026

3 days ago

1.6yr newer

Knowledge Cutoff

When training data ends

Gemini 3.5 Flash-Lite has a documented knowledge cutoff of 2026-03-31, while DeepSeek VL2's cutoff date is not specified.

We can confirm Gemini 3.5 Flash-Lite's training data extends to 2026-03-31, but cannot make a direct comparison without DeepSeek VL2's cutoff date.

DeepSeek VL2

—

Gemini 3.5 Flash-Lite

Mar 2026

Provider Availability

DeepSeek VL2 is available from Replicate. Gemini 3.5 Flash-Lite is available from Google.

DeepSeek VL2

replicate logo
Replicate

Gemini 3.5 Flash-Lite

google logo
Google
Input Price:Input: $0.30/1MOutput Price:Output: $2.50/1M
* Prices shown are per million tokens

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)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against DeepSeek VL2 and Gemini 3.5 Flash-Lite side-by-side, then vote on the output you prefer.

DeepSeek VL2
✓ Preferred
Gemini 3.5 Flash-Lite
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2
Google
Gemini 3.5 Flash-Lite

FAQ

Common questions about DeepSeek VL2 vs Gemini 3.5 Flash-Lite.

Which is better, DeepSeek VL2 or Gemini 3.5 Flash-Lite?

DeepSeek VL2 (DeepSeek) and Gemini 3.5 Flash-Lite (Google) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DeepSeek VL2 compare to Gemini 3.5 Flash-Lite in benchmarks?

DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%. Gemini 3.5 Flash-Lite scores CharXiv-R: 76.5%, OSWorld-Verified: 74.0%, SWE-Bench Pro: 54.2%, Terminal-Bench 2.1: 54.0%, MLE-Bench: 39.2%.

What are the context window sizes for DeepSeek VL2 and Gemini 3.5 Flash-Lite?

DeepSeek VL2 supports 129K tokens and Gemini 3.5 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 3.5 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 3.5 Flash-Lite?

DeepSeek VL2 is developed by DeepSeek and Gemini 3.5 Flash-Lite is developed by Google.

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