Model Comparison

K-EXAONE-236B-A23B vs QvQ-72B-Preview

Comparing K-EXAONE-236B-A23B and QvQ-72B-Preview across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

K-EXAONE-236B-A23B 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
Wed Apr 15 2026 • llm-stats.com
LG AI Research
K-EXAONE-236B-A23B
Input tokens$0.60
Output tokens$1.00
Best providerUnknown Organization
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

162.6B diff

K-EXAONE-236B-A23B has 162.6B more parameters than QvQ-72B-Preview, making it 221.5% larger.

LG AI Research
K-EXAONE-236B-A23B
236.0Bparameters
Alibaba Cloud / Qwen Team
QvQ-72B-Preview
73.4Bparameters
236.0B
K-EXAONE-236B-A23B
73.4B
QvQ-72B-Preview

Context Window

Maximum input and output token capacity

Only K-EXAONE-236B-A23B specifies input context (32,768 tokens). Only K-EXAONE-236B-A23B specifies output context (32,768 tokens).

LG AI Research
K-EXAONE-236B-A23B
Input32,768 tokens
Output32,768 tokens
Alibaba Cloud / Qwen Team
QvQ-72B-Preview
Input- tokens
Output- tokens
Wed Apr 15 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

QvQ-72B-Preview supports multimodal inputs, whereas K-EXAONE-236B-A23B does not.

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

K-EXAONE-236B-A23B

Text
Images
Audio
Video

QvQ-72B-Preview

Text
Images
Audio
Video

License

Usage and distribution terms

K-EXAONE-236B-A23B is licensed under a proprietary license, while QvQ-72B-Preview uses Qwen.

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

K-EXAONE-236B-A23B

Proprietary

Closed source

QvQ-72B-Preview

Qwen

Open weights

Release Timeline

When each model was launched

K-EXAONE-236B-A23B was released on 2025-12-31, while QvQ-72B-Preview was released on 2024-12-25.

K-EXAONE-236B-A23B is 12 months newer than QvQ-72B-Preview.

K-EXAONE-236B-A23B

Dec 31, 2025

3 months ago

1.0yr newer
QvQ-72B-Preview

Dec 25, 2024

1.3 years ago

Knowledge Cutoff

When training data ends

K-EXAONE-236B-A23B has a documented knowledge cutoff of 2025-10-01, while QvQ-72B-Preview's cutoff date is not specified.

We can confirm K-EXAONE-236B-A23B's training data extends to 2025-10-01, but cannot make a direct comparison without QvQ-72B-Preview's cutoff date.

K-EXAONE-236B-A23B

Oct 2025

QvQ-72B-Preview

—

Outputs Comparison

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Key Takeaways

LG AI Research
Larger context window (32,768 tokens)
Alibaba Cloud / Qwen Team

QvQ-72B-Preview

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs
Has open weights

Detailed Comparison

AI Model Comparison Table
Feature
LG AI Research
K-EXAONE-236B-A23B
Alibaba Cloud / Qwen Team
QvQ-72B-Preview

FAQ

Common questions about K-EXAONE-236B-A23B vs QvQ-72B-Preview

K-EXAONE-236B-A23B (LG AI Research) 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.
K-EXAONE-236B-A23B scores AIME 2025: 92.8%, MMMLU: 85.7%, MMLU-Pro: 83.8%, LiveCodeBench v6: 80.7%, t2-bench: 73.2%. QvQ-72B-Preview scores MathVista: 71.4%, MMMU: 70.3%, MathVision: 35.9%, OlympiadBench: 20.4%.
K-EXAONE-236B-A23B supports 33K 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 (Proprietary vs Qwen). See the full comparison above for benchmark-by-benchmark results.
K-EXAONE-236B-A23B is developed by LG AI Research and QvQ-72B-Preview is developed by Alibaba Cloud / Qwen Team.