The AI arena is free today

Open Superagent

DeepSeek-V4-Flash-0731 vs QvQ-72B-Preview

DeepSeek-V4-Flash-0731 leads the LLM Stats Score 44.7 to 7.9.

DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

DeepSeek-V4-Flash-0731 leads the overall LLM Stats Score 44.7 to 7.9, ranking #35 overall.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-V4-Flash-0731

  • overall performance matters — it scores 44.7 and ranks #35 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Jul 2026

Choose QvQ-72B-Preview

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

At a glance

The differences that matter most.

DeepSeek-V4-Flash-0731
DeepSeek
QvQ-72B-Preview
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
44.7
#35
7.9
#281
Reasoning
42.3
#45
8.2
#275
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.06 / M
— / M
Output price
$0.18 / M
— / M
Context window
1,048,576
—

Individual benchmarks

9 reported for DeepSeek-V4-Flash-0731 · 4 for QvQ-72B-Preview

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.

Human preference

Blind head-to-head votes and playground preference scores

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 (1,048,576 tokens).

DeepSeek
DeepSeek-V4-Flash-0731
Input1,048,576 tokens
Output1,048,576 tokens
Alibaba Cloud / Qwen Team
QvQ-72B-Preview
Input- tokens
Output- tokens
Sun Sep 13 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

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

1 months ago

1.6yr newer
QvQ-72B-Preview

Dec 25, 2024

1.7 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→

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

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 leads the LLM Stats Score 44.7 to 7.9. DeepSeek-V4-Flash-0731 is made by DeepSeek and QvQ-72B-Preview is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

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 LLM Stats Score (44.7 vs 7.9), 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.

Related comparisons