K-EXAONE-236B-A23B vs Qwen3.8 Max
Qwen3.8 Max significantly outperforms across most benchmarks. K-EXAONE-236B-A23B is 3.5x cheaper per token.
LG AI Research · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
K-EXAONE-236B-A23B outperforms in 0 benchmarks, while Qwen3.8 Max is better at 1 benchmark (IFBench). Qwen3.8 Max significantly outperforms across most benchmarks.
On price, K-EXAONE-236B-A23B is roughly 3.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3.8 Max also accepts a larger context window (256,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current benchmark, pricing, and model metadata for 2026.
Choose K-EXAONE-236B-A23B
- cost matters — it's about 3.5x cheaper per token
Choose Qwen3.8 Max
- you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
- you process long inputs — it offers a 256,000 token context window
- 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.
Performance Benchmarks
Comparative analysis across standard metrics
K-EXAONE-236B-A23B outperforms in 0 benchmarks, while Qwen3.8 Max is better at 1 benchmark (IFBench).
Qwen3.8 Max significantly outperforms across most benchmarks.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, K-EXAONE-236B-A23B ($0.60/1M tokens) is 2.8x cheaper than Qwen3.8 Max ($1.65/1M tokens).
For output processing, K-EXAONE-236B-A23B ($1.00/1M tokens) is 5.0x cheaper than Qwen3.8 Max ($4.95/1M tokens).
In conclusion, Qwen3.8 Max is more expensive than K-EXAONE-236B-A23B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Qwen3.8 Max has 2164.0B more parameters than K-EXAONE-236B-A23B, making it 916.9% larger.
Context Window
Maximum input and output token capacity
Qwen3.8 Max accepts 256,000 input tokens compared to K-EXAONE-236B-A23B's 32,768 tokens. Qwen3.8 Max can generate longer responses up to 131,072 tokens, while K-EXAONE-236B-A23B is limited to 32,768 tokens.
Input Capabilities
Supported data types and modalities
Qwen3.8 Max supports multimodal inputs, whereas K-EXAONE-236B-A23B does not.
Qwen3.8 Max can handle both text and other forms of data like images, making it suitable for multimodal applications.
K-EXAONE-236B-A23B
Qwen3.8 Max
License
Usage and distribution terms
K-EXAONE-236B-A23B is licensed under a proprietary license, while Qwen3.8 Max uses Qwen3.8-Max License.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Qwen3.8-Max License
Open weights
Release Timeline
When each model was launched
K-EXAONE-236B-A23B was released on 2025-12-31, while Qwen3.8 Max was released on 2026-08-02.
Qwen3.8 Max is 7 months newer than K-EXAONE-236B-A23B.
Dec 31, 2025
7 months ago
Aug 2, 2026
3 weeks ago
7mo newerKnowledge Cutoff
When training data ends
K-EXAONE-236B-A23B has a documented knowledge cutoff of 2025-10-01, while Qwen3.8 Max'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 Max's cutoff date.
Oct 2025
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Provider Availability
K-EXAONE-236B-A23B is available from FriendliAI. Qwen3.8 Max is available from DeepInfra, Fireworks, Novita, Together.
K-EXAONE-236B-A23B
Qwen3.8 Max
Outputs Comparison
Judge for yourself.
Run your own prompts against K-EXAONE-236B-A23B and Qwen3.8 Max side-by-side, then vote on the output you prefer.
FAQ
Common questions about K-EXAONE-236B-A23B vs Qwen3.8 Max.