Model Comparison

DeepSeek-V4-Flash-0731 vs QvQ-72B-PreviewWhich is better in 2026?

Comparing DeepSeek-V4-Flash-0731 and QvQ-72B-Preview across benchmarks, pricing, and capabilities.

Verdict: DeepSeek-V4-Flash-0731 vs QvQ-72B-Preview — which is better?

DeepSeek-V4-Flash-0731 (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-V4-Flash-0731 if…

  • you want the most recent training data — it shipped Jul 2026

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-V4-Flash-0731 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

230.6B diff

DeepSeek-V4-Flash-0731 has 230.6B more parameters than QvQ-72B-Preview, making it 314.2% larger.

DeepSeek
DeepSeek-V4-Flash-0731
304.0Bparameters
Alibaba Cloud / Qwen Team
QvQ-72B-Preview
73.4Bparameters
304.0B
DeepSeek-V4-Flash-0731
73.4B
QvQ-72B-Preview

Context Window

Maximum input and output token capacity

Only DeepSeek-V4-Flash-0731 specifies input context (1,048,576 tokens). Only DeepSeek-V4-Flash-0731 specifies output context (65,536 tokens).

DeepSeek
DeepSeek-V4-Flash-0731
Input1,048,576 tokens
Output65,536 tokens
Alibaba Cloud / Qwen Team
QvQ-72B-Preview
Input- tokens
Output- tokens
Tue Aug 04 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

QvQ-72B-Preview supports multimodal inputs, whereas DeepSeek-V4-Flash-0731 does not.

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

DeepSeek-V4-Flash-0731

Text
Images
Audio
Video

QvQ-72B-Preview

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4-Flash-0731 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-V4-Flash-0731

MIT

Open weights

QvQ-72B-Preview

Qwen

Open weights

Release Timeline

When each model was launched

DeepSeek-V4-Flash-0731 was released on 2026-07-31, while QvQ-72B-Preview was released on 2024-12-25.

DeepSeek-V4-Flash-0731 is 19 months newer than QvQ-72B-Preview.

DeepSeek-V4-Flash-0731

Jul 31, 2026

4 days ago

1.6yr 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 (1,048,576 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-V4-Flash-0731 and QvQ-72B-Preview side-by-side, then vote on the output you prefer.

DeepSeek-V4-Flash-0731
✓ Preferred
QvQ-72B-Preview
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V4-Flash-0731
Alibaba Cloud / Qwen Team
QvQ-72B-Preview

FAQ

Common questions about DeepSeek-V4-Flash-0731 vs QvQ-72B-Preview.

Which is better, DeepSeek-V4-Flash-0731 or QvQ-72B-Preview?

DeepSeek-V4-Flash-0731 (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-V4-Flash-0731 compare to QvQ-72B-Preview in benchmarks?

DeepSeek-V4-Flash-0731 scores Terminal-Bench 2.1: 82.7%, CyberGym: 76.7%, Toolathlon: 70.3%, DSBench-FullStack: 68.7%, DSBench-Hard: 59.6%. QvQ-72B-Preview scores MathVista: 71.4%, MMMU: 70.3%, MathVision: 35.9%, OlympiadBench: 20.4%.

What are the context window sizes for DeepSeek-V4-Flash-0731 and QvQ-72B-Preview?

DeepSeek-V4-Flash-0731 supports 1.0M 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-V4-Flash-0731 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-V4-Flash-0731 and QvQ-72B-Preview?

DeepSeek-V4-Flash-0731 is developed by DeepSeek and QvQ-72B-Preview is developed by Alibaba Cloud / Qwen Team.

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