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DeepSeek R1 Zero vs Qwen2.5 VL 32B Instruct

DeepSeek R1 Zero significantly outperforms across most benchmarks.

DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

DeepSeek R1 Zero outperforms in 1 benchmarks (GPQA), while Qwen2.5 VL 32B Instruct is better at 0 benchmarks. DeepSeek R1 Zero significantly outperforms across most benchmarks.

Based on current benchmark, pricing, and model metadata for 2026.

Choose DeepSeek R1 Zero

  • you want the strongest raw capability — it leads on 1 of 1 shared benchmarks

Choose Qwen2.5 VL 32B Instruct

  • you want the most recent training data — it shipped Feb 2025

At a glance

The differences that matter most.

Benchmark wins
1 of 1
0 of 1
Input price
— / M
— / M
Output price
— / M
— / M
Context window
Released
Jan 2025
Feb 2025
License
MIT
Apache 2.0

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek R1 Zero outperforms in 1 benchmarks (GPQA), while Qwen2.5 VL 32B Instruct is better at 0 benchmarks.

DeepSeek R1 Zero significantly outperforms across most benchmarks.

Tue Aug 25 2026 • llm-stats.com

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

637.5B diff

DeepSeek R1 Zero has 637.5B more parameters than Qwen2.5 VL 32B Instruct, making it 1903.0% larger.

DeepSeek
DeepSeek R1 Zero
671.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5 VL 32B Instruct
33.5Bparameters
671.0B
DeepSeek R1 Zero
33.5B
Qwen2.5 VL 32B Instruct

Input Capabilities

Supported data types and modalities

Qwen2.5 VL 32B Instruct supports multimodal inputs, whereas DeepSeek R1 Zero does not.

Qwen2.5 VL 32B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek R1 Zero

Text
Images
Audio
Video

Qwen2.5 VL 32B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek R1 Zero is licensed under MIT, while Qwen2.5 VL 32B Instruct uses Apache 2.0.

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

DeepSeek R1 Zero

MIT

Open weights

Qwen2.5 VL 32B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Zero was released on 2025-01-20, while Qwen2.5 VL 32B Instruct was released on 2025-02-28.

Qwen2.5 VL 32B Instruct is 1 month newer than DeepSeek R1 Zero.

DeepSeek R1 Zero

Jan 20, 2025

1.6 years ago

Qwen2.5 VL 32B Instruct

Feb 28, 2025

1.5 years ago

1mo newer

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 Qwen2.5 VL 32B Instruct side-by-side, then vote on the output you prefer.

DeepSeek R1 Zero
✓ Preferred
Qwen2.5 VL 32B Instruct
Open in Playground

FAQ

Common questions about DeepSeek R1 Zero vs Qwen2.5 VL 32B Instruct.

Which is better, DeepSeek R1 Zero or Qwen2.5 VL 32B Instruct?

DeepSeek R1 Zero significantly outperforms across most benchmarks. DeepSeek R1 Zero is made by DeepSeek and Qwen2.5 VL 32B Instruct is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek R1 Zero compare to Qwen2.5 VL 32B Instruct in benchmarks?

DeepSeek R1 Zero scores MATH-500: 95.9%, AIME 2024: 86.7%, GPQA: 73.3%, LiveCodeBench: 50.0%. Qwen2.5 VL 32B Instruct scores DocVQA: 94.8%, Android Control Low_EM: 93.3%, HumanEval: 91.5%, ScreenSpot: 88.5%, MBPP: 84.0%.

What are the main differences between DeepSeek R1 Zero and Qwen2.5 VL 32B Instruct?

Key differences include multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek R1 Zero and Qwen2.5 VL 32B Instruct?

DeepSeek R1 Zero is developed by DeepSeek and Qwen2.5 VL 32B Instruct is developed by Alibaba Cloud / Qwen Team.