Model Comparison

DeepSeek-V3.2-Exp vs QvQ-72B-PreviewWhich is better in 2026?

Comparing DeepSeek-V3.2-Exp and QvQ-72B-Preview across benchmarks, pricing, and capabilities.

Verdict: DeepSeek-V3.2-Exp vs QvQ-72B-Preview — which is better?

DeepSeek-V3.2-Exp (by DeepSeek) and QvQ-72B-Preview (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-Exp if…

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

Choose QvQ-72B-Preview 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-Exp and QvQ-72B-Previewdon'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

611.6B diff

DeepSeek-V3.2-Exp has 611.6B more parameters than QvQ-72B-Preview, making it 833.2% larger.

DeepSeek
DeepSeek-V3.2-Exp
685.0Bparameters
Alibaba Cloud / Qwen Team
QvQ-72B-Preview
73.4Bparameters
685.0B
DeepSeek-V3.2-Exp
73.4B
QvQ-72B-Preview

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
QvQ-72B-Preview
Input- tokens
Output- tokens
Tue Jul 21 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

QvQ-72B-Preview supports multimodal inputs, whereas DeepSeek-V3.2-Exp does not.

QvQ-72B-Preview 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

QvQ-72B-Preview

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.2-Exp is licensed under MIT, while QvQ-72B-Preview uses Qwen.

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

DeepSeek-V3.2-Exp

MIT

Open weights

QvQ-72B-Preview

Qwen

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2-Exp was released on 2025-09-29, while QvQ-72B-Preview was released on 2024-12-25.

DeepSeek-V3.2-Exp is 9 months newer than QvQ-72B-Preview.

DeepSeek-V3.2-Exp

Sep 29, 2025

9 months ago

9mo newer
QvQ-72B-Preview

Dec 25, 2024

1.6 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

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

QvQ-72B-Preview

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against DeepSeek-V3.2-Exp and QvQ-72B-Preview side-by-side, then vote on the output you prefer.

DeepSeek-V3.2-Exp
✓ Preferred
QvQ-72B-Preview
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2-Exp
Alibaba Cloud / Qwen Team
QvQ-72B-Preview

FAQ

Common questions about DeepSeek-V3.2-Exp vs QvQ-72B-Preview.

Which is better, DeepSeek-V3.2-Exp or QvQ-72B-Preview?

DeepSeek-V3.2-Exp (DeepSeek) and QvQ-72B-Preview (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-Exp compare to QvQ-72B-Preview in benchmarks?

DeepSeek-V3.2-Exp scores SimpleQA: 97.1%, AIME 2025: 89.3%, MMLU-Pro: 85.0%, HMMT 2025: 83.6%, GPQA: 79.9%. QvQ-72B-Preview scores MathVista: 71.4%, MMMU: 70.3%, MathVision: 35.9%, OlympiadBench: 20.4%.

What are the context window sizes for DeepSeek-V3.2-Exp and QvQ-72B-Preview?

DeepSeek-V3.2-Exp supports 164K tokens and QvQ-72B-Preview 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-Exp and QvQ-72B-Preview?

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

Who makes DeepSeek-V3.2-Exp and QvQ-72B-Preview?

DeepSeek-V3.2-Exp is developed by DeepSeek and QvQ-72B-Preview is developed by Alibaba Cloud / Qwen Team.

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