Model Comparison

DeepSeek-V3.2-Speciale vs Qwen2.5 VL 72B InstructWhich is better in 2026?

Comparing DeepSeek-V3.2-Speciale and Qwen2.5 VL 72B Instruct across benchmarks, pricing, and capabilities.

Verdict: DeepSeek-V3.2-Speciale vs Qwen2.5 VL 72B Instruct — which is better?

DeepSeek-V3.2-Speciale (by DeepSeek) and Qwen2.5 VL 72B Instruct (by Alibaba Cloud / Qwen Team) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

Choose DeepSeek-V3.2-Speciale if…

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

Choose Qwen2.5 VL 72B Instruct if…

  • you are already invested in the Alibaba Cloud / Qwen Team ecosystem

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V3.2-Speciale and Qwen2.5 VL 72B Instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Model Size

Parameter count comparison

613.0B diff

DeepSeek-V3.2-Speciale has 613.0B more parameters than Qwen2.5 VL 72B Instruct, making it 851.4% larger.

DeepSeek
DeepSeek-V3.2-Speciale
685.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5 VL 72B Instruct
72.0Bparameters
685.0B
DeepSeek-V3.2-Speciale
72.0B
Qwen2.5 VL 72B Instruct

Context Window

Maximum input and output token capacity

Only DeepSeek-V3.2-Speciale specifies input context (131,072 tokens). Only DeepSeek-V3.2-Speciale specifies output context (131,072 tokens).

DeepSeek
DeepSeek-V3.2-Speciale
Input131,072 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen2.5 VL 72B Instruct
Input- tokens
Output- tokens
Fri Jul 10 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen2.5 VL 72B Instruct supports multimodal inputs, whereas DeepSeek-V3.2-Speciale does not.

Qwen2.5 VL 72B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V3.2-Speciale

Text
Images
Audio
Video

Qwen2.5 VL 72B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.2-Speciale is licensed under MIT, while Qwen2.5 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-Speciale

MIT

Open weights

Qwen2.5 VL 72B Instruct

tongyi-qianwen

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2-Speciale was released on 2025-12-01, while Qwen2.5 VL 72B Instruct was released on 2025-01-26.

DeepSeek-V3.2-Speciale is 10 months newer than Qwen2.5 VL 72B Instruct.

DeepSeek-V3.2-Speciale

Dec 1, 2025

7 months ago

10mo newer
Qwen2.5 VL 72B Instruct

Jan 26, 2025

1.4 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

Key Takeaways

Larger context window (131,072 tokens)
Alibaba Cloud / Qwen Team

Qwen2.5 VL 72B Instruct

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against DeepSeek-V3.2-Speciale and Qwen2.5 VL 72B Instruct side-by-side, then vote on the output you prefer.

DeepSeek-V3.2-Speciale
✓ Preferred
Qwen2.5 VL 72B Instruct
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2-Speciale
Alibaba Cloud / Qwen Team
Qwen2.5 VL 72B Instruct

FAQ

Common questions about DeepSeek-V3.2-Speciale vs Qwen2.5 VL 72B Instruct.

Which is better, DeepSeek-V3.2-Speciale or Qwen2.5 VL 72B Instruct?

DeepSeek-V3.2-Speciale (DeepSeek) and Qwen2.5 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.

How does DeepSeek-V3.2-Speciale compare to Qwen2.5 VL 72B Instruct in benchmarks?

DeepSeek-V3.2-Speciale scores HMMT 2025: 99.2%, AIME 2025: 96.0%, CodeForces: 90.0%, t2-bench: 80.3%, SWE-Bench Verified: 73.1%. Qwen2.5 VL 72B Instruct scores DocVQA: 96.4%, Android Control Low_EM: 93.7%, ChartQA: 89.5%, OCRBench: 88.5%, AI2D: 88.4%.

What are the context window sizes for DeepSeek-V3.2-Speciale and Qwen2.5 VL 72B Instruct?

DeepSeek-V3.2-Speciale supports 131K tokens and Qwen2.5 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.

What are the main differences between DeepSeek-V3.2-Speciale and Qwen2.5 VL 72B Instruct?

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

Who makes DeepSeek-V3.2-Speciale and Qwen2.5 VL 72B Instruct?

DeepSeek-V3.2-Speciale is developed by DeepSeek and Qwen2.5 VL 72B Instruct is developed by Alibaba Cloud / Qwen Team.