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K-EXAONE-236B-A23B vs Qwen3.8-27B

Qwen3.8-27B significantly outperforms across most benchmarks.

LG AI Research · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

K-EXAONE-236B-A23B outperforms in 0 benchmarks, while Qwen3.8-27B is better at 2 benchmarks (IFBench, LiveCodeBench v6). Qwen3.8-27B significantly outperforms across most benchmarks.

Based on current benchmark, pricing, and model metadata for 2026.

Choose K-EXAONE-236B-A23B

  • you want predictable pricing at $0.60/M input and $1.00/M output

Choose Qwen3.8-27B

  • you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
  • you want the most recent training data — it shipped Aug 2026
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Benchmark wins
0 of 2
2 of 2
Input price
$0.60 / M
— / M
Output price
$1.00 / M
— / M
Context window
32,768
Released
Dec 2025
Aug 2026
License
Proprietary
Apache 2.0

Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

K-EXAONE-236B-A23B outperforms in 0 benchmarks, while Qwen3.8-27B is better at 2 benchmarks (IFBench, LiveCodeBench v6).

Qwen3.8-27B significantly outperforms across most benchmarks.

Mon Aug 24 2026 • llm-stats.com

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

208.2B diff

K-EXAONE-236B-A23B has 208.2B more parameters than Qwen3.8-27B, making it 749.5% larger.

LG AI Research
K-EXAONE-236B-A23B
236.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3.8-27B
27.8Bparameters
236.0B
K-EXAONE-236B-A23B
27.8B
Qwen3.8-27B

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
Qwen3.8-27B
Input- tokens
Output- tokens
Mon Aug 24 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3.8-27B supports multimodal inputs, whereas K-EXAONE-236B-A23B does not.

Qwen3.8-27B 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

Qwen3.8-27B

Text
Images
Audio
Video

License

Usage and distribution terms

K-EXAONE-236B-A23B is licensed under a proprietary license, while Qwen3.8-27B uses Apache 2.0.

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

K-EXAONE-236B-A23B

Proprietary

Closed source

Qwen3.8-27B

Apache 2.0

Open weights

Release Timeline

When each model was launched

K-EXAONE-236B-A23B was released on 2025-12-31, while Qwen3.8-27B was released on 2026-08-14.

Qwen3.8-27B is 8 months newer than K-EXAONE-236B-A23B.

K-EXAONE-236B-A23B

Dec 31, 2025

7 months ago

Qwen3.8-27B

Aug 14, 2026

1 weeks ago

7mo newer

Knowledge Cutoff

When training data ends

K-EXAONE-236B-A23B has a documented knowledge cutoff of 2025-10-01, while Qwen3.8-27B'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 Qwen3.8-27B's cutoff date.

K-EXAONE-236B-A23B

Oct 2025

Qwen3.8-27B

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against K-EXAONE-236B-A23B and Qwen3.8-27B side-by-side, then vote on the output you prefer.

K-EXAONE-236B-A23B
✓ Preferred
Qwen3.8-27B
Open in Playground

FAQ

Common questions about K-EXAONE-236B-A23B vs Qwen3.8-27B.

Which is better, K-EXAONE-236B-A23B or Qwen3.8-27B?

Qwen3.8-27B significantly outperforms across most benchmarks. K-EXAONE-236B-A23B is made by LG AI Research and Qwen3.8-27B is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does K-EXAONE-236B-A23B compare to Qwen3.8-27B in benchmarks?

K-EXAONE-236B-A23B scores AIME 2025: 92.8%, MMMLU: 85.7%, MMLU-Pro: 83.8%, LiveCodeBench v6: 80.7%, t2-bench: 73.2%. Qwen3.8-27B scores MathVision: 94.6%, OmniDocBench 1.5: 91.1%, LiveCodeBench v6: 90.3%, CharXiv-R: 90.2%, GPQA: 89.2%.

What are the context window sizes for K-EXAONE-236B-A23B and Qwen3.8-27B?

K-EXAONE-236B-A23B supports 33K tokens and Qwen3.8-27B 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 K-EXAONE-236B-A23B and Qwen3.8-27B?

Key differences include multimodal support (no vs yes), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes K-EXAONE-236B-A23B and Qwen3.8-27B?

K-EXAONE-236B-A23B is developed by LG AI Research and Qwen3.8-27B is developed by Alibaba Cloud / Qwen Team.