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DeepSeek-V4.1-Flash vs QvQ-72B-Preview

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 7.9.

DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to 7.9, ranking #12 overall.

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

Choose DeepSeek-V4.1-Flash

  • overall performance matters — it scores 51.8 and ranks #12 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Sep 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-V4.1-Flash
DeepSeek
QvQ-72B-Preview
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
51.8
#12
7.9
#281
Reasoning
48.9
#17
8.2
#275
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.22 / M
— / M
Output price
$0.66 / M
— / M
Context window
1,040,000
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
DeepSeek-V4.1-Flash
QvQ-72B-Preview
Math
35.2#43
9.6#253
Vision
29.5#31
6.3#147
Multimodal
34.3#13
9.6#118
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

20 reported for DeepSeek-V4.1-Flash · 4 for QvQ-72B-Preview

No common benchmarks found

DeepSeek-V4.1-Flash 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

689.8B diff

DeepSeek-V4.1-Flash has 689.8B more parameters than QvQ-72B-Preview, making it 939.8% larger.

DeepSeek
DeepSeek-V4.1-Flash
763.2Bparameters
Alibaba Cloud / Qwen Team
QvQ-72B-Preview
73.4Bparameters
763.2B
DeepSeek-V4.1-Flash
73.4B
QvQ-72B-Preview

Context Window

Maximum input and output token capacity

Only DeepSeek-V4.1-Flash specifies input context (1,040,000 tokens). Only DeepSeek-V4.1-Flash specifies output context (393,216 tokens).

DeepSeek
DeepSeek-V4.1-Flash
Input1,040,000 tokens
Output393,216 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

Both DeepSeek-V4.1-Flash and QvQ-72B-Preview support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

DeepSeek-V4.1-Flash

Text
Images
Audio
Video

QvQ-72B-Preview

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash 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-V4.1-Flash

MIT

Open weights

QvQ-72B-Preview

Qwen

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash was released on 2026-09-10, while QvQ-72B-Preview was released on 2024-12-25.

DeepSeek-V4.1-Flash is 21 months newer than QvQ-72B-Preview.

DeepSeek-V4.1-Flash

Sep 10, 2026

3 days ago

1.7yr 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-V4.1-Flash and QvQ-72B-Preview side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash
✓ Preferred
QvQ-72B-Preview
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash vs QvQ-72B-Preview.

Which is better, DeepSeek-V4.1-Flash or QvQ-72B-Preview?

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 7.9. DeepSeek-V4.1-Flash 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-V4.1-Flash compare to QvQ-72B-Preview in benchmarks?

DeepSeek-V4.1-Flash scores CodeForces: 100.0%, GPQA: 90.9%, Terminal-Bench 2.1: 90.6%, BabyVision: 89.6%, CyberGym: 88.1%. QvQ-72B-Preview scores MathVista: 71.4%, MMMU: 70.3%, MathVision: 35.9%, OlympiadBench: 20.4%.

What are the context window sizes for DeepSeek-V4.1-Flash and QvQ-72B-Preview?

DeepSeek-V4.1-Flash 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-V4.1-Flash and QvQ-72B-Preview?

Key differences include LLM Stats Score (51.8 vs 7.9), licensing (MIT vs Qwen). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash and QvQ-72B-Preview?

DeepSeek-V4.1-Flash is developed by DeepSeek and QvQ-72B-Preview is developed by Alibaba Cloud / Qwen Team.

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