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

Comparing DeepSeek-V3 and Qwen2-VL-72B-Instruct across benchmarks, pricing, and capabilities.

DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

DeepSeek-V3 and Qwen2-VL-72B-Instruct trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

Based on current benchmark, 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.

Benchmark wins
Input price
$0.27 / M
— / M
Output price
$1.10 / M
— / M
Context window
131,072
Released
Dec 2024
Aug 2024
License
MIT + Model License (Commercial use allowed)
tongyi-qianwen

Performance Benchmarks

Comparative analysis across standard metrics

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.

Arena Performance

Playground indexes and blind 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
Thu Aug 27 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

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 (DeepSeek) and Qwen2-VL-72B-Instruct (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 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 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.