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DeepSeek VL2 vs Gemini 1.5 Flash

DeepSeek VL2 and Gemini 1.5 Flash are closely matched at 3.2 and 6.2 on the LLM Stats Score.

DeepSeek · Google · Updated for 2026

Which is better?

DeepSeek VL2 and Gemini 1.5 Flash are closely matched on the overall LLM Stats Score at 3.2 and 6.2.

In the 2 individual benchmarks reported for both models, Gemini 1.5 Flash wins 2; this is a narrower head-to-head signal than the composite indexes.

Gemini 1.5 Flash also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek VL2

  • you want the most recent training data — it shipped Dec 2024
  • you need open weights you can self-host or fine-tune

Choose Gemini 1.5 Flash

  • you value its reported benchmark strengths — it wins 2 of 2 exact shared results
  • you process long inputs — it offers a 1,048,576 token context window

At a glance

The differences that matter most.

DeepSeek VL2
DeepSeek
Gemini 1.5 Flash
Google
Core performance indexes
LLM Stats Score
3.2
#298
6.2
#281
Reasoning
-1.5
#315
5.8
#279
Cost, coverage & limits
Benchmark wins
0 of 2
2 of 2
Input price
— / M
$0.15 / M
Output price
— / M
$0.60 / M
Context window
129,280
1,048,576

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
DeepSeek VL2
Gemini 1.5 Flash
Vision
2.7#162
5.9#146
Multimodal
5.7#132
9.5#116
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

14 reported for DeepSeek VL2 · 22 for Gemini 1.5 Flash

2 shared

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

Gemini 1.5 Flash significantly outperforms across most benchmarks.

Thu Sep 03 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Gemini 1.5 Flash 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 1.5 Flash is limited to 8,192 tokens.

DeepSeek
DeepSeek VL2
Input129,280 tokens
Output129,280 tokens
Google
Gemini 1.5 Flash
Input1,048,576 tokens
Output8,192 tokens
Thu Sep 03 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both DeepSeek VL2 and Gemini 1.5 Flash support multimodal inputs.

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

DeepSeek VL2

Text
Images
Audio
Video

Gemini 1.5 Flash

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 is licensed under deepseek, while Gemini 1.5 Flash 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 1.5 Flash

Proprietary

Closed source

Release Timeline

When each model was launched

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

DeepSeek VL2 is 8 months newer than Gemini 1.5 Flash.

DeepSeek VL2

Dec 13, 2024

1.7 years ago

7mo newer
Gemini 1.5 Flash

May 1, 2024

2.3 years ago

Knowledge Cutoff

When training data ends

Gemini 1.5 Flash has a documented knowledge cutoff of 2023-11-01, while DeepSeek VL2'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's cutoff date.

DeepSeek VL2

—

Gemini 1.5 Flash

Nov 2023

Provider Availability

DeepSeek VL2 is available from Replicate. Gemini 1.5 Flash is available from Google.

DeepSeek VL2

replicate logo
Replicate

Gemini 1.5 Flash

google logo
Google
Input Price:Input: $0.15/1MOutput Price:Output: $0.60/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek VL2 and Gemini 1.5 Flash side-by-side, then vote on the output you prefer.

DeepSeek VL2
✓ Preferred
Gemini 1.5 Flash
Open in Playground

FAQ

Common questions about DeepSeek VL2 vs Gemini 1.5 Flash.

Which is better, DeepSeek VL2 or Gemini 1.5 Flash?

DeepSeek VL2 and Gemini 1.5 Flash are closely matched on the LLM Stats Score at 3.2 and 6.2. DeepSeek VL2 is made by DeepSeek and Gemini 1.5 Flash is made by Google. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

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

DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%. Gemini 1.5 Flash scores XSTest: 97.0%, FLEURS: 90.4%, HellaSwag: 86.5%, GSM8k: 86.2%, BIG-Bench Hard: 85.5%.

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

DeepSeek VL2 supports 129K tokens and Gemini 1.5 Flash 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 1.5 Flash?

Key differences include LLM Stats Score (3.2 vs 6.2), 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 1.5 Flash?

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

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