Model Comparison

DeepSeek-V3.2-Exp vs Qwen2-VL-72B-Instruct

Comparing DeepSeek-V3.2-Exp and Qwen2-VL-72B-Instruct across benchmarks, pricing, and capabilities.

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V3.2-Exp 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 Apr 21 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2-Exp
Input tokens$0.27
Output tokens$0.41
Best providerNovita
Alibaba Cloud / Qwen Team
Qwen2-VL-72B-Instruct
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue

Model Size

Parameter count comparison

611.6B diff

DeepSeek-V3.2-Exp has 611.6B more parameters than Qwen2-VL-72B-Instruct, making it 833.2% larger.

DeepSeek
DeepSeek-V3.2-Exp
685.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2-VL-72B-Instruct
73.4Bparameters
685.0B
DeepSeek-V3.2-Exp
73.4B
Qwen2-VL-72B-Instruct

Context Window

Maximum input and output token capacity

Only DeepSeek-V3.2-Exp specifies input context (163,840 tokens). Only DeepSeek-V3.2-Exp specifies output context (65,536 tokens).

DeepSeek
DeepSeek-V3.2-Exp
Input163,840 tokens
Output65,536 tokens
Alibaba Cloud / Qwen Team
Qwen2-VL-72B-Instruct
Input- tokens
Output- tokens
Tue Apr 21 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen2-VL-72B-Instruct supports multimodal inputs, whereas DeepSeek-V3.2-Exp does not.

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

DeepSeek-V3.2-Exp

Text
Images
Audio
Video

Qwen2-VL-72B-Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.2-Exp 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-V3.2-Exp

MIT

Open weights

Qwen2-VL-72B-Instruct

tongyi-qianwen

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2-Exp was released on 2025-09-29, while Qwen2-VL-72B-Instruct was released on 2024-08-29.

DeepSeek-V3.2-Exp is 13 months newer than Qwen2-VL-72B-Instruct.

DeepSeek-V3.2-Exp

Sep 29, 2025

6 months ago

1.1yr 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-V3.2-Exp'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-V3.2-Exp's cutoff date.

DeepSeek-V3.2-Exp

Qwen2-VL-72B-Instruct

Jun 2023

Outputs Comparison

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Key Takeaways

Larger context window (163,840 tokens)
Alibaba Cloud / Qwen Team

Qwen2-VL-72B-Instruct

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2-Exp
Alibaba Cloud / Qwen Team
Qwen2-VL-72B-Instruct

FAQ

Common questions about DeepSeek-V3.2-Exp vs Qwen2-VL-72B-Instruct

DeepSeek-V3.2-Exp (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-V3.2-Exp scores SimpleQA: 97.1%, AIME 2025: 89.3%, MMLU-Pro: 85.0%, HMMT 2025: 83.6%, GPQA: 79.9%. Qwen2-VL-72B-Instruct scores DocVQAtest: 96.5%, VCR_en_easy: 91.9%, ChartQA: 88.3%, OCRBench: 87.7%, MMBench_test: 86.5%.
DeepSeek-V3.2-Exp supports 164K tokens and Qwen2-VL-72B-Instruct supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include multimodal support (no vs yes), licensing (MIT vs tongyi-qianwen). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3.2-Exp is developed by DeepSeek and Qwen2-VL-72B-Instruct is developed by Alibaba Cloud / Qwen Team.