EXAONE 4.5 33B vs Qwen3 VL 235B A22B Instruct
EXAONE 4.5 33B shows notably better performance in the majority of benchmarks.
LG AI Research · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
EXAONE 4.5 33B outperforms in 6 benchmarks (AIME 2025, IFEval, LiveCodeBench v6, MathVista-Mini, MMLU-Pro, MMMU-Pro), while Qwen3 VL 235B A22B Instruct is better at 2 benchmarks (AI2D, MMStar). EXAONE 4.5 33B shows notably better performance in the majority of benchmarks.
Based on current benchmark, pricing, and model metadata for 2026.
Choose EXAONE 4.5 33B
- you want the strongest raw capability — it leads on 6 of 8 shared benchmarks
- you want the most recent training data — it shipped Apr 2026
Choose Qwen3 VL 235B A22B Instruct
- 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
EXAONE 4.5 33B outperforms in 6 benchmarks (AIME 2025, IFEval, LiveCodeBench v6, MathVista-Mini, MMLU-Pro, MMMU-Pro), while Qwen3 VL 235B A22B Instruct is better at 2 benchmarks (AI2D, MMStar).
EXAONE 4.5 33B shows notably better performance in the majority of benchmarks.
Arena Performance
Playground indexes and blind preference scores
Model Size
Parameter count comparison
Qwen3 VL 235B A22B Instruct has 203.0B more parameters than EXAONE 4.5 33B, making it 615.2% larger.
Context Window
Maximum input and output token capacity
Only Qwen3 VL 235B A22B Instruct specifies input context (262,144 tokens). Only Qwen3 VL 235B A22B Instruct specifies output context (262,144 tokens).
Input Capabilities
Supported data types and modalities
Both EXAONE 4.5 33B and Qwen3 VL 235B A22B Instruct support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
EXAONE 4.5 33B
Qwen3 VL 235B A22B Instruct
License
Usage and distribution terms
EXAONE 4.5 33B is licensed under a proprietary license, while Qwen3 VL 235B A22B Instruct 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 Qwen3 VL 235B A22B Instruct was released on 2025-09-22.
EXAONE 4.5 33B is 7 months newer than Qwen3 VL 235B A22B Instruct.
Apr 9, 2026
4 months ago
6mo newerSep 22, 2025
11 months ago
Knowledge Cutoff
When training data ends
EXAONE 4.5 33B has a documented knowledge cutoff of 2024-12-01, while Qwen3 VL 235B A22B Instruct'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 Qwen3 VL 235B A22B Instruct's cutoff date.
Dec 2024
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Outputs Comparison
Judge for yourself.
Run your own prompts against EXAONE 4.5 33B and Qwen3 VL 235B A22B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about EXAONE 4.5 33B vs Qwen3 VL 235B A22B Instruct.