K-EXAONE-236B-A23B vs Qwen3 235B A22B
K-EXAONE-236B-A23B leads the LLM Stats Score 26.2 to 15.6. Qwen3 235B A22B is 7.0x cheaper per token.
LG AI Research · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
K-EXAONE-236B-A23B leads the overall LLM Stats Score 26.2 to 15.6, ranking #151 overall.
In the 3 individual benchmarks reported for both models, K-EXAONE-236B-A23B wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, Qwen3 235B A22B is roughly 7.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3 235B A22B also accepts a larger context window (128,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose K-EXAONE-236B-A23B
- overall performance matters — it scores 26.2 and ranks #151 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 3 exact shared results
- you want the most recent training data — it shipped Dec 2025
Choose Qwen3 235B A22B
- cost matters — it's about 7.0x cheaper per token
- you process long inputs — it offers a 128,000 token context window
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
6 reported for K-EXAONE-236B-A23B · 23 for Qwen3 235B A22B
K-EXAONE-236B-A23B outperforms in 2 benchmarks (AIME 2025, MMLU-Pro), while Qwen3 235B A22B is better at 1 benchmark (MMMLU).
K-EXAONE-236B-A23B shows notably better performance in the majority of benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, K-EXAONE-236B-A23B ($0.60/1M tokens) is 6.0x more expensive than Qwen3 235B A22B ($0.10/1M tokens).
For output processing, K-EXAONE-236B-A23B ($1.00/1M tokens) is 10.0x more expensive than Qwen3 235B A22B ($0.10/1M tokens).
In conclusion, K-EXAONE-236B-A23B is more expensive than Qwen3 235B A22B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
K-EXAONE-236B-A23B has 1.0B more parameters than Qwen3 235B A22B, making it 0.4% larger.
Context Window
Maximum input and output token capacity
Qwen3 235B A22B accepts 128,000 input tokens compared to K-EXAONE-236B-A23B's 32,768 tokens. Qwen3 235B A22B can generate longer responses up to 128,000 tokens, while K-EXAONE-236B-A23B is limited to 32,768 tokens.
License
Usage and distribution terms
K-EXAONE-236B-A23B is licensed under a proprietary license, while Qwen3 235B A22B uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
K-EXAONE-236B-A23B was released on 2025-12-31, while Qwen3 235B A22B was released on 2025-04-29.
K-EXAONE-236B-A23B is 8 months newer than Qwen3 235B A22B.
Dec 31, 2025
8 months ago
8mo newerApr 29, 2025
1.4 years ago
Knowledge Cutoff
When training data ends
K-EXAONE-236B-A23B has a documented knowledge cutoff of 2025-10-01, while Qwen3 235B A22B'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 235B A22B's cutoff date.
Oct 2025
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Provider Availability
K-EXAONE-236B-A23B is available from FriendliAI. Qwen3 235B A22B is available from Fireworks, DeepInfra, Novita, Together.
K-EXAONE-236B-A23B
Qwen3 235B A22B
Outputs Comparison
Judge for yourself.
Run your own prompts against K-EXAONE-236B-A23B and Qwen3 235B A22B side-by-side, then vote on the output you prefer.
FAQ
Common questions about K-EXAONE-236B-A23B vs Qwen3 235B A22B.