EXAONE 4.5 33B vs Hy4 preview
Hy4 preview leads the LLM Stats Score 51.1 to 26.3.
LG AI Research · Tencent · Updated for 2026
Which is better?
Hy4 preview leads the overall LLM Stats Score 51.1 to 26.3, ranking #14 overall.
In the 1 individual benchmarks reported for both models, Hy4 preview wins 1; this is a narrower head-to-head signal than the composite indexes.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose EXAONE 4.5 33B
- you are already invested in the LG AI Research ecosystem
Choose Hy4 preview
- overall performance matters — it scores 51.1 and ranks #14 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- 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.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
15 reported for EXAONE 4.5 33B · 32 for Hy4 preview
EXAONE 4.5 33B outperforms in 0 benchmarks, while Hy4 preview is better at 1 benchmark (GPQA).
Hy4 preview significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
Hy4 preview has 737.0B more parameters than EXAONE 4.5 33B, making it 2233.3% larger.
Input capabilities
Documented input modalities across available providers
EXAONE 4.5 33B supports multimodal inputs, whereas Hy4 preview does not.
EXAONE 4.5 33B can handle both text and other forms of data like images, making it suitable for multimodal applications.
EXAONE 4.5 33B
Hy4 preview
License
Usage and distribution terms
EXAONE 4.5 33B is licensed under a proprietary license, while Hy4 preview 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
EXAONE 4.5 33B was released on 2026-04-09, while Hy4 preview was released on 2026-08-28.
Hy4 preview is 5 months newer than EXAONE 4.5 33B.
Apr 9, 2026
4 months ago
Aug 28, 2026
1 weeks ago
4mo newerKnowledge Cutoff
When training data ends
EXAONE 4.5 33B has a documented knowledge cutoff of 2024-12-01, while Hy4 preview's cutoff date is not specified.
We can confirm EXAONE 4.5 33B's training data extends to 2024-12-01, but cannot make a direct comparison without Hy4 preview's cutoff date.
Dec 2024
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Outputs Comparison
Judge for yourself.
Run your own prompts against EXAONE 4.5 33B and Hy4 preview side-by-side, then vote on the output you prefer.
FAQ
Common questions about EXAONE 4.5 33B vs Hy4 preview.