Model Comparison

K-EXAONE-236B-A23B vs Qwen3-Coder

Comparing K-EXAONE-236B-A23B and Qwen3-Coder across benchmarks, pricing, and capabilities.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

K-EXAONE-236B-A23B and Qwen3-Coder 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

Qwen3-Coder costs less

For input processing, K-EXAONE-236B-A23B ($0.60/1M tokens) is 3.3x more expensive than Qwen3-Coder ($0.18/1M tokens).

For output processing, K-EXAONE-236B-A23B ($1.00/1M tokens) is 5.6x more expensive than Qwen3-Coder ($0.18/1M tokens).

In conclusion, K-EXAONE-236B-A23B is more expensive than Qwen3-Coder.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Fri Apr 17 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
Qwen3-Coder
Input tokens$0.18
Output tokens$0.18
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

244.0B diff

Qwen3-Coder has 244.0B more parameters than K-EXAONE-236B-A23B, making it 103.4% larger.

LG AI Research
K-EXAONE-236B-A23B
236.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3-Coder
480.0Bparameters
236.0B
K-EXAONE-236B-A23B
480.0B
Qwen3-Coder

Context Window

Maximum input and output token capacity

Qwen3-Coder accepts 256,000 input tokens compared to K-EXAONE-236B-A23B's 32,768 tokens. Qwen3-Coder can generate longer responses up to 256,000 tokens, while K-EXAONE-236B-A23B is limited to 32,768 tokens.

LG AI Research
K-EXAONE-236B-A23B
Input32,768 tokens
Output32,768 tokens
Alibaba Cloud / Qwen Team
Qwen3-Coder
Input256,000 tokens
Output256,000 tokens
Fri Apr 17 2026 • llm-stats.com

License

Usage and distribution terms

K-EXAONE-236B-A23B is licensed under a proprietary license, while Qwen3-Coder 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-Coder

Apache 2.0

Open weights

Release Timeline

When each model was launched

K-EXAONE-236B-A23B was released on 2025-12-31, while Qwen3-Coder was released on 2025-01-01.

K-EXAONE-236B-A23B is 12 months newer than Qwen3-Coder.

K-EXAONE-236B-A23B

Dec 31, 2025

3 months ago

12mo newer
Qwen3-Coder

Jan 1, 2025

1.3 years ago

Knowledge Cutoff

When training data ends

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

K-EXAONE-236B-A23B

Oct 2025

Qwen3-Coder

—

Provider Availability

K-EXAONE-236B-A23B is available from FriendliAI. Qwen3-Coder is available from DeepInfra, Fireworks.

K-EXAONE-236B-A23B

friendli logo
Unknown Organization
Input Price:Input: $0.60/1MOutput Price:Output: $1.00/1M

Qwen3-Coder

deepinfra logo
Deepinfra
Input Price:Input: $0.18/1MOutput Price:Output: $0.18/1M
fireworks logo
Fireworks
Input Price:Input: $0.25/1MOutput Price:Output: $0.25/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

LG AI Research
Alibaba Cloud / Qwen Team

Qwen3-Coder

View details

Alibaba Cloud / Qwen Team

Larger context window (256,000 tokens)
Less expensive input tokens
Less expensive output tokens
Has open weights

Detailed Comparison

AI Model Comparison Table
Feature
LG AI Research
K-EXAONE-236B-A23B
Alibaba Cloud / Qwen Team
Qwen3-Coder

FAQ

Common questions about K-EXAONE-236B-A23B vs Qwen3-Coder

K-EXAONE-236B-A23B (LG AI Research) and Qwen3-Coder (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%.
Qwen3-Coder is 3.3x cheaper for input tokens. K-EXAONE-236B-A23B costs $0.60/M input and $1.00/M output via friendli. Qwen3-Coder costs $0.18/M input and $0.18/M output via deepinfra.
K-EXAONE-236B-A23B supports 33K tokens and Qwen3-Coder supports 256K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (33K vs 256K), input pricing ($0.60 vs $0.18/M), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
K-EXAONE-236B-A23B is developed by LG AI Research and Qwen3-Coder is developed by Alibaba Cloud / Qwen Team.