Model Comparison

DeepSeek-V3 vs QvQ-72B-Preview

Comparing DeepSeek-V3 and QvQ-72B-Preview across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V3 and QvQ-72B-Preview don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Sat Apr 04 2026 • llm-stats.com
DeepSeek
DeepSeek-V3
Input tokens$0.27
Output tokens$1.10
Best providerDeepSeek
Alibaba Cloud / Qwen Team
QvQ-72B-Preview
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

597.6B diff

DeepSeek-V3 has 597.6B more parameters than QvQ-72B-Preview, making it 814.2% larger.

DeepSeek
DeepSeek-V3
671.0Bparameters
Alibaba Cloud / Qwen Team
QvQ-72B-Preview
73.4Bparameters
671.0B
DeepSeek-V3
73.4B
QvQ-72B-Preview

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
QvQ-72B-Preview
Input- tokens
Output- tokens
Sat Apr 04 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

QvQ-72B-Preview supports multimodal inputs, whereas DeepSeek-V3 does not.

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

DeepSeek-V3

Text
Images
Audio
Video

QvQ-72B-Preview

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while QvQ-72B-Preview uses Qwen.

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

QvQ-72B-Preview

Qwen

Open weights

Release Timeline

When each model was launched

Both models were released on 2024-12-25.

They likely represent similar generations of model development.

DeepSeek-V3

Dec 25, 2024

1.3 years ago

QvQ-72B-Preview

Dec 25, 2024

1.3 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 (131,072 tokens)
Alibaba Cloud / Qwen Team

QvQ-72B-Preview

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3
Alibaba Cloud / Qwen Team
QvQ-72B-Preview

FAQ

Common questions about DeepSeek-V3 vs QvQ-72B-Preview

DeepSeek-V3 (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.
DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. QvQ-72B-Preview scores MathVista: 71.4%, MMMU: 70.3%, MathVision: 35.9%, OlympiadBench: 20.4%.
DeepSeek-V3 supports 131K 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.
Key differences include multimodal support (no vs yes), licensing (MIT + Model License (Commercial use allowed) vs Qwen). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3 is developed by DeepSeek and QvQ-72B-Preview is developed by Alibaba Cloud / Qwen Team.