Model Comparison

K-EXAONE-236B-A23B vs Qwen2 72B Instruct

K-EXAONE-236B-A23B significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

K-EXAONE-236B-A23B outperforms in 1 benchmarks (MMLU-Pro), while Qwen2 72B Instruct is better at 0 benchmarks.

K-EXAONE-236B-A23B significantly outperforms across most benchmarks.

Wed Apr 15 2026 • llm-stats.com

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
Qwen2 72B Instruct
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

164.0B diff

K-EXAONE-236B-A23B has 164.0B more parameters than Qwen2 72B Instruct, making it 227.8% larger.

LG AI Research
K-EXAONE-236B-A23B
236.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2 72B Instruct
72.0Bparameters
236.0B
K-EXAONE-236B-A23B
72.0B
Qwen2 72B Instruct

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
Qwen2 72B Instruct
Input- tokens
Output- tokens
Wed Apr 15 2026 • llm-stats.com

License

Usage and distribution terms

K-EXAONE-236B-A23B is licensed under a proprietary license, while Qwen2 72B Instruct uses tongyi-qianwen.

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

K-EXAONE-236B-A23B

Proprietary

Closed source

Qwen2 72B Instruct

tongyi-qianwen

Open weights

Release Timeline

When each model was launched

K-EXAONE-236B-A23B was released on 2025-12-31, while Qwen2 72B Instruct was released on 2024-07-23.

K-EXAONE-236B-A23B is 18 months newer than Qwen2 72B Instruct.

K-EXAONE-236B-A23B

Dec 31, 2025

3 months ago

1.4yr newer
Qwen2 72B Instruct

Jul 23, 2024

1.7 years ago

Knowledge Cutoff

When training data ends

K-EXAONE-236B-A23B has a documented knowledge cutoff of 2025-10-01, while Qwen2 72B Instruct'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 Qwen2 72B Instruct's cutoff date.

K-EXAONE-236B-A23B

Oct 2025

Qwen2 72B Instruct

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Outputs Comparison

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Key Takeaways

LG AI Research
Larger context window (32,768 tokens)
Higher MMLU-Pro score (83.8% vs 64.4%)
Alibaba Cloud / Qwen Team

Qwen2 72B Instruct

View details

Alibaba Cloud / Qwen Team

Has open weights

Detailed Comparison

AI Model Comparison Table
Feature
LG AI Research
K-EXAONE-236B-A23B
Alibaba Cloud / Qwen Team
Qwen2 72B Instruct

FAQ

Common questions about K-EXAONE-236B-A23B vs Qwen2 72B Instruct

K-EXAONE-236B-A23B significantly outperforms across most benchmarks. K-EXAONE-236B-A23B is made by LG AI Research and Qwen2 72B Instruct is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
K-EXAONE-236B-A23B scores AIME 2025: 92.8%, MMMLU: 85.7%, MMLU-Pro: 83.8%, LiveCodeBench v6: 80.7%, t2-bench: 73.2%. Qwen2 72B Instruct scores GSM8k: 91.1%, CMMLU: 90.1%, HellaSwag: 87.6%, HumanEval: 86.0%, Winogrande: 85.1%.
K-EXAONE-236B-A23B supports 33K tokens and Qwen2 72B Instruct 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 licensing (Proprietary vs tongyi-qianwen). See the full comparison above for benchmark-by-benchmark results.
K-EXAONE-236B-A23B is developed by LG AI Research and Qwen2 72B Instruct is developed by Alibaba Cloud / Qwen Team.