Model Comparison

DeepSeek-V3 vs K-EXAONE-236B-A23B

K-EXAONE-236B-A23B significantly outperforms across most benchmarks. DeepSeek-V3 is 1.5x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek-V3 outperforms in 0 benchmarks, while K-EXAONE-236B-A23B is better at 1 benchmark (MMLU-Pro).

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

Fri Apr 17 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-V3 costs less

For input processing, DeepSeek-V3 ($0.27/1M tokens) is 2.2x cheaper than K-EXAONE-236B-A23B ($0.60/1M tokens).

For output processing, DeepSeek-V3 ($1.10/1M tokens) is 1.1x more expensive than K-EXAONE-236B-A23B ($1.00/1M tokens).

In conclusion, K-EXAONE-236B-A23B is more expensive than DeepSeek-V3.*

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

Lowest available price from all providers
Fri Apr 17 2026 • llm-stats.com
DeepSeek
DeepSeek-V3
Input tokens$0.27
Output tokens$1.10
Best providerDeepSeek
LG AI Research
K-EXAONE-236B-A23B
Input tokens$0.60
Output tokens$1.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

435.0B diff

DeepSeek-V3 has 435.0B more parameters than K-EXAONE-236B-A23B, making it 184.3% larger.

DeepSeek
DeepSeek-V3
671.0Bparameters
LG AI Research
K-EXAONE-236B-A23B
236.0Bparameters
671.0B
DeepSeek-V3
236.0B
K-EXAONE-236B-A23B

Context Window

Maximum input and output token capacity

DeepSeek-V3 accepts 131,072 input tokens compared to K-EXAONE-236B-A23B's 32,768 tokens. DeepSeek-V3 can generate longer responses up to 131,072 tokens, while K-EXAONE-236B-A23B is limited to 32,768 tokens.

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
LG AI Research
K-EXAONE-236B-A23B
Input32,768 tokens
Output32,768 tokens
Fri Apr 17 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while K-EXAONE-236B-A23B uses a proprietary license.

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

DeepSeek-V3

MIT + Model License (Commercial use allowed)

Open weights

K-EXAONE-236B-A23B

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while K-EXAONE-236B-A23B was released on 2025-12-31.

K-EXAONE-236B-A23B is 12 months newer than DeepSeek-V3.

DeepSeek-V3

Dec 25, 2024

1.3 years ago

K-EXAONE-236B-A23B

Dec 31, 2025

3 months ago

1.0yr newer

Knowledge Cutoff

When training data ends

K-EXAONE-236B-A23B has a documented knowledge cutoff of 2025-10-01, while DeepSeek-V3'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 DeepSeek-V3's cutoff date.

DeepSeek-V3

—

K-EXAONE-236B-A23B

Oct 2025

Provider Availability

DeepSeek-V3 is available from DeepSeek. K-EXAONE-236B-A23B is available from FriendliAI.

DeepSeek-V3

deepseek logo
DeepSeek
Input Price:Input: $0.27/1MOutput Price:Output: $1.10/1M

K-EXAONE-236B-A23B

friendli logo
Unknown Organization
Input Price:Input: $0.60/1MOutput Price:Output: $1.00/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Larger context window (131,072 tokens)
Less expensive input tokens
Has open weights
LG AI Research
Less expensive output tokens
Higher MMLU-Pro score (83.8% vs 75.9%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3
LG AI Research
K-EXAONE-236B-A23B

FAQ

Common questions about DeepSeek-V3 vs K-EXAONE-236B-A23B

K-EXAONE-236B-A23B significantly outperforms across most benchmarks. DeepSeek-V3 is made by DeepSeek and K-EXAONE-236B-A23B is made by LG AI Research. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. K-EXAONE-236B-A23B scores AIME 2025: 92.8%, MMMLU: 85.7%, MMLU-Pro: 83.8%, LiveCodeBench v6: 80.7%, t2-bench: 73.2%.
DeepSeek-V3 is 2.2x cheaper for input tokens. DeepSeek-V3 costs $0.27/M input and $1.10/M output via deepseek. K-EXAONE-236B-A23B costs $0.60/M input and $1.00/M output via friendli.
DeepSeek-V3 supports 131K tokens and K-EXAONE-236B-A23B supports 33K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (131K vs 33K), input pricing ($0.27 vs $0.60/M), licensing (MIT + Model License (Commercial use allowed) vs Proprietary). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3 is developed by DeepSeek and K-EXAONE-236B-A23B is developed by LG AI Research.