Model Comparison

K-EXAONE-236B-A23B vs Qwen3 32B

K-EXAONE-236B-A23B significantly outperforms across most benchmarks. Qwen3 32B is 4.7x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

K-EXAONE-236B-A23B outperforms in 1 benchmarks (AIME 2025), while Qwen3 32B is better at 0 benchmarks.

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

Thu Apr 16 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3 32B costs less

For input processing, K-EXAONE-236B-A23B ($0.60/1M tokens) is 6.0x more expensive than Qwen3 32B ($0.10/1M tokens).

For output processing, K-EXAONE-236B-A23B ($1.00/1M tokens) is 3.3x more expensive than Qwen3 32B ($0.30/1M tokens).

In conclusion, K-EXAONE-236B-A23B is more expensive than Qwen3 32B.*

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

Lowest available price from all providers
Thu Apr 16 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 32B
Input tokens$0.10
Output tokens$0.30
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

203.2B diff

K-EXAONE-236B-A23B has 203.2B more parameters than Qwen3 32B, making it 619.5% larger.

LG AI Research
K-EXAONE-236B-A23B
236.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 32B
32.8Bparameters
236.0B
K-EXAONE-236B-A23B
32.8B
Qwen3 32B

Context Window

Maximum input and output token capacity

Qwen3 32B accepts 128,000 input tokens compared to K-EXAONE-236B-A23B's 32,768 tokens. Qwen3 32B can generate longer responses up to 128,000 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 32B
Input128,000 tokens
Output128,000 tokens
Thu Apr 16 2026 • llm-stats.com

License

Usage and distribution terms

K-EXAONE-236B-A23B is licensed under a proprietary license, while Qwen3 32B 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 32B

Apache 2.0

Open weights

Release Timeline

When each model was launched

K-EXAONE-236B-A23B was released on 2025-12-31, while Qwen3 32B was released on 2025-04-29.

K-EXAONE-236B-A23B is 8 months newer than Qwen3 32B.

K-EXAONE-236B-A23B

Dec 31, 2025

3 months ago

8mo newer
Qwen3 32B

Apr 29, 2025

11 months ago

Knowledge Cutoff

When training data ends

K-EXAONE-236B-A23B has a documented knowledge cutoff of 2025-10-01, while Qwen3 32B'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 32B's cutoff date.

K-EXAONE-236B-A23B

Oct 2025

Qwen3 32B

—

Provider Availability

K-EXAONE-236B-A23B is available from FriendliAI. Qwen3 32B is available from DeepInfra, Novita, Sambanova.

K-EXAONE-236B-A23B

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

Qwen3 32B

deepinfra logo
Deepinfra
Input Price:Input: $0.10/1MOutput Price:Output: $0.30/1M
novita logo
Novita
Input Price:Input: $0.10/1MOutput Price:Output: $0.44/1M
sambanova logo
Sambanova
Input Price:Input: $0.40/1MOutput Price:Output: $0.80/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

LG AI Research
Higher AIME 2025 score (92.8% vs 72.9%)
Alibaba Cloud / Qwen Team

Qwen3 32B

View details

Alibaba Cloud / Qwen Team

Larger context window (128,000 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 32B

FAQ

Common questions about K-EXAONE-236B-A23B vs Qwen3 32B

K-EXAONE-236B-A23B significantly outperforms across most benchmarks. K-EXAONE-236B-A23B is made by LG AI Research and Qwen3 32B 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%. Qwen3 32B scores Arena Hard: 93.8%, AIME 2024: 81.4%, LiveBench: 74.9%, MultiLF: 73.0%, AIME 2025: 72.9%.
Qwen3 32B is 6.0x cheaper for input tokens. K-EXAONE-236B-A23B costs $0.60/M input and $1.00/M output via friendli. Qwen3 32B costs $0.10/M input and $0.30/M output via deepinfra.
K-EXAONE-236B-A23B supports 33K tokens and Qwen3 32B supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (33K vs 128K), input pricing ($0.60 vs $0.10/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 32B is developed by Alibaba Cloud / Qwen Team.