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DeepSeek-V3 vs Qwen2-VL-72B-Instruct

DeepSeek-V3 and Qwen2-VL-72B-Instruct are closely matched at 15.7 and 14.3 on the LLM Stats Score.

DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

DeepSeek-V3 and Qwen2-VL-72B-Instruct are closely matched on the overall LLM Stats Score at 15.7 and 14.3.

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

Choose DeepSeek-V3

  • you want the most recent training data — it shipped Dec 2024

Choose Qwen2-VL-72B-Instruct

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

At a glance

The differences that matter most.

DeepSeek-V3
DeepSeek
Qwen2-VL-72B-Instruct
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
15.7
#227
14.3
#236
Reasoning
14.8
#226
11.6
#251
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.27 / M
— / M
Output price
$0.89 / M
— / M
Context window
131,072
—

Individual benchmarks

20 reported for DeepSeek-V3 · 15 for Qwen2-VL-72B-Instruct

No common benchmarks found

DeepSeek-V3 and Qwen2-VL-72B-Instructdon'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

597.6B diff

DeepSeek-V3 has 597.6B more parameters than Qwen2-VL-72B-Instruct, making it 814.2% larger.

DeepSeek
DeepSeek-V3
671.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2-VL-72B-Instruct
73.4Bparameters
671.0B
DeepSeek-V3
73.4B
Qwen2-VL-72B-Instruct

Context Window

Maximum input and output token capacity

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

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen2-VL-72B-Instruct
Input- tokens
Output- tokens
Fri Sep 11 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

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

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

DeepSeek-V3

Text
Images
Audio
Video

Qwen2-VL-72B-Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while Qwen2-VL-72B-Instruct uses tongyi-qianwen.

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

DeepSeek-V3

MIT + Model License (Commercial use allowed)

Open weights

Qwen2-VL-72B-Instruct

tongyi-qianwen

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while Qwen2-VL-72B-Instruct was released on 2024-08-29.

DeepSeek-V3 is 4 months newer than Qwen2-VL-72B-Instruct.

DeepSeek-V3

Dec 25, 2024

1.7 years ago

3mo newer
Qwen2-VL-72B-Instruct

Aug 29, 2024

2.0 years ago

Knowledge Cutoff

When training data ends

Qwen2-VL-72B-Instruct has a documented knowledge cutoff of 2023-06-30, while DeepSeek-V3's cutoff date is not specified.

We can confirm Qwen2-VL-72B-Instruct's training data extends to 2023-06-30, but cannot make a direct comparison without DeepSeek-V3's cutoff date.

DeepSeek-V3

—

Qwen2-VL-72B-Instruct

Jun 2023

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

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

DeepSeek-V3
✓ Preferred
Qwen2-VL-72B-Instruct
Open in Playground

FAQ

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

Which is better, DeepSeek-V3 or Qwen2-VL-72B-Instruct?

DeepSeek-V3 and Qwen2-VL-72B-Instruct are closely matched on the LLM Stats Score at 15.7 and 14.3. DeepSeek-V3 is made by DeepSeek and Qwen2-VL-72B-Instruct 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-V3 compare to Qwen2-VL-72B-Instruct in benchmarks?

DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. Qwen2-VL-72B-Instruct scores DocVQAtest: 96.5%, VCR_en_easy: 91.9%, ChartQA: 88.3%, OCRBench: 87.7%, MMBench: 86.5%.

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

DeepSeek-V3 supports 131K tokens and Qwen2-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 and Qwen2-VL-72B-Instruct?

Key differences include LLM Stats Score (15.7 vs 14.3), multimodal support (no vs yes), licensing (MIT + Model License (Commercial use allowed) vs tongyi-qianwen). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3 and Qwen2-VL-72B-Instruct?

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

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