The AI arena is free today

Open Superagent

DeepSeek R1 Zero vs DeepSeek VL2 Small

DeepSeek R1 Zero leads the LLM Stats Score 16.1 to 1.4.

DeepSeek · DeepSeek · Updated for 2026

Which is better?

DeepSeek R1 Zero leads the overall LLM Stats Score 16.1 to 1.4, ranking #213 overall.

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

Choose DeepSeek R1 Zero

  • overall performance matters — it scores 16.1 and ranks #213 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Jan 2025

Choose DeepSeek VL2 Small

  • you are already invested in the DeepSeek ecosystem

At a glance

The differences that matter most.

DeepSeek R1 Zero
DeepSeek
DeepSeek VL2 Small
DeepSeek
Core performance indexes
LLM Stats Score
16.1
#213
1.4
#309
Reasoning
16.4
#204
-3.6
#326
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
— / M
Output price
— / M
— / M
Context window
—
—

Individual benchmarks

4 reported for DeepSeek R1 Zero · 14 for DeepSeek VL2 Small

No common benchmarks found

DeepSeek R1 Zero and DeepSeek VL2 Smalldon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

655.0B diff

DeepSeek R1 Zero has 655.0B more parameters than DeepSeek VL2 Small, making it 4093.8% larger.

DeepSeek
DeepSeek R1 Zero
671.0Bparameters
DeepSeek
DeepSeek VL2 Small
16.0Bparameters
671.0B
DeepSeek R1 Zero
16.0B
DeepSeek VL2 Small

Input capabilities

Documented input modalities across available providers

DeepSeek VL2 Small supports multimodal inputs, whereas DeepSeek R1 Zero does not.

DeepSeek VL2 Small can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek R1 Zero

Text
Images
Audio
Video

DeepSeek VL2 Small

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek R1 Zero is licensed under MIT, while DeepSeek VL2 Small uses deepseek.

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

DeepSeek R1 Zero

MIT

Open weights

DeepSeek VL2 Small

deepseek

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Zero was released on 2025-01-20, while DeepSeek VL2 Small was released on 2024-12-13.

DeepSeek R1 Zero is 1 month newer than DeepSeek VL2 Small.

DeepSeek R1 Zero

Jan 20, 2025

1.6 years ago

1mo newer
DeepSeek VL2 Small

Dec 13, 2024

1.7 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek R1 Zero and DeepSeek VL2 Small side-by-side, then vote on the output you prefer.

DeepSeek R1 Zero
✓ Preferred
DeepSeek VL2 Small
Open in Playground

FAQ

Common questions about DeepSeek R1 Zero vs DeepSeek VL2 Small.

Which is better, DeepSeek R1 Zero or DeepSeek VL2 Small?

DeepSeek R1 Zero leads the LLM Stats Score 16.1 to 1.4. DeepSeek R1 Zero is made by DeepSeek and DeepSeek VL2 Small is made by DeepSeek. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek R1 Zero compare to DeepSeek VL2 Small in benchmarks?

DeepSeek R1 Zero scores MATH-500: 95.9%, AIME 2024: 86.7%, GPQA: 73.3%, LiveCodeBench: 50.0%. DeepSeek VL2 Small scores DocVQA: 92.3%, ChartQA: 84.5%, OCRBench: 83.4%, TextVQA: 83.4%, MMBench: 80.3%.

What are the main differences between DeepSeek R1 Zero and DeepSeek VL2 Small?

Key differences include LLM Stats Score (16.1 vs 1.4), multimodal support (no vs yes), licensing (MIT vs deepseek). See the full comparison above for benchmark-by-benchmark results.

Related comparisons