Model Comparison

DeepSeek R1 Distill Qwen 1.5B vs Qwen2-VL-72B-Instruct

Comparing DeepSeek R1 Distill Qwen 1.5B and Qwen2-VL-72B-Instruct across benchmarks, pricing, and capabilities.

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek R1 Distill Qwen 1.5B and Qwen2-VL-72B-Instruct don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Tue Mar 31 2026 • llm-stats.com
DeepSeek
DeepSeek R1 Distill Qwen 1.5B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Alibaba Cloud / Qwen Team
Qwen2-VL-72B-Instruct
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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Model Size

Parameter count comparison

71.6B diff

Qwen2-VL-72B-Instruct has 71.6B more parameters than DeepSeek R1 Distill Qwen 1.5B, making it 4023.6% larger.

DeepSeek
DeepSeek R1 Distill Qwen 1.5B
1.8Bparameters
Alibaba Cloud / Qwen Team
Qwen2-VL-72B-Instruct
73.4Bparameters
1.8B
DeepSeek R1 Distill Qwen 1.5B
73.4B
Qwen2-VL-72B-Instruct

Input Capabilities

Supported data types and modalities

Qwen2-VL-72B-Instruct supports multimodal inputs, whereas DeepSeek R1 Distill Qwen 1.5B does not.

Qwen2-VL-72B-Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek R1 Distill Qwen 1.5B

Text
Images
Audio
Video

Qwen2-VL-72B-Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek R1 Distill Qwen 1.5B is licensed under MIT, while Qwen2-VL-72B-Instruct uses tongyi-qianwen.

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

DeepSeek R1 Distill Qwen 1.5B

MIT

Open weights

Qwen2-VL-72B-Instruct

tongyi-qianwen

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Qwen 1.5B was released on 2025-01-20, while Qwen2-VL-72B-Instruct was released on 2024-08-29.

DeepSeek R1 Distill Qwen 1.5B is 5 months newer than Qwen2-VL-72B-Instruct.

DeepSeek R1 Distill Qwen 1.5B

Jan 20, 2025

1.2 years ago

4mo newer
Qwen2-VL-72B-Instruct

Aug 29, 2024

1.6 years ago

Knowledge Cutoff

When training data ends

Qwen2-VL-72B-Instruct has a documented knowledge cutoff of 2023-06-30, while DeepSeek R1 Distill Qwen 1.5B's cutoff date is not specified.

We can confirm Qwen2-VL-72B-Instruct's training data extends to 2023-06-30, but cannot make a direct comparison without DeepSeek R1 Distill Qwen 1.5B's cutoff date.

DeepSeek R1 Distill Qwen 1.5B

Qwen2-VL-72B-Instruct

Jun 2023

Outputs Comparison

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Key Takeaways

Alibaba Cloud / Qwen Team

Qwen2-VL-72B-Instruct

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs

Detailed Comparison

FAQ

Common questions about DeepSeek R1 Distill Qwen 1.5B vs Qwen2-VL-72B-Instruct

DeepSeek R1 Distill Qwen 1.5B (DeepSeek) and Qwen2-VL-72B-Instruct (Alibaba Cloud / Qwen Team) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
DeepSeek R1 Distill Qwen 1.5B scores MATH-500: 83.9%, AIME 2024: 52.7%, GPQA: 33.8%, LiveCodeBench: 16.9%. Qwen2-VL-72B-Instruct scores DocVQAtest: 96.5%, VCR_en_easy: 91.9%, ChartQA: 88.3%, OCRBench: 87.7%, MMBench_test: 86.5%.
Key differences include multimodal support (no vs yes), licensing (MIT vs tongyi-qianwen). See the full comparison above for benchmark-by-benchmark results.
DeepSeek R1 Distill Qwen 1.5B is developed by DeepSeek and Qwen2-VL-72B-Instruct is developed by Alibaba Cloud / Qwen Team.