EXAONE 4.5 33B vs Qwen3-235B-A22B-Instruct-2507
EXAONE 4.5 33B and Qwen3-235B-A22B-Instruct-2507 are closely matched at 26.0 and 24.2 on the LLM Stats Score.
LG AI Research · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
EXAONE 4.5 33B and Qwen3-235B-A22B-Instruct-2507 are closely matched on the overall LLM Stats Score at 26.0 and 24.2.
In the 7 individual benchmarks reported for both models, EXAONE 4.5 33B wins 7; 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 value its reported benchmark strengths — it wins 7 of 7 exact shared results
- you want the most recent training data — it shipped Apr 2026
Choose Qwen3-235B-A22B-Instruct-2507
- 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 · 25 for Qwen3-235B-A22B-Instruct-2507
EXAONE 4.5 33B outperforms in 7 benchmarks (AIME 2025, GPQA, IFEval, LiveCodeBench v6, MMLU-Pro, Tau2 Airline, Tau2 Retail), while Qwen3-235B-A22B-Instruct-2507 is better at 0 benchmarks.
EXAONE 4.5 33B significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
Qwen3-235B-A22B-Instruct-2507 has 202.0B more parameters than EXAONE 4.5 33B, making it 612.1% larger.
Context Window
Maximum input and output token capacity
Only Qwen3-235B-A22B-Instruct-2507 specifies input context (262,144 tokens). Only Qwen3-235B-A22B-Instruct-2507 specifies output context (262,144 tokens).
Input capabilities
Documented input modalities across available providers
EXAONE 4.5 33B supports multimodal inputs, whereas Qwen3-235B-A22B-Instruct-2507 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
Qwen3-235B-A22B-Instruct-2507
License
Usage and distribution terms
EXAONE 4.5 33B is licensed under a proprietary license, while Qwen3-235B-A22B-Instruct-2507 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 Qwen3-235B-A22B-Instruct-2507 was released on 2025-07-22.
EXAONE 4.5 33B is 9 months newer than Qwen3-235B-A22B-Instruct-2507.
Apr 9, 2026
5 months ago
8mo newerJul 22, 2025
1.2 years ago
Knowledge Cutoff
When training data ends
EXAONE 4.5 33B has a documented knowledge cutoff of 2024-12-01, while Qwen3-235B-A22B-Instruct-2507'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 Qwen3-235B-A22B-Instruct-2507's cutoff date.
Dec 2024
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Outputs Comparison
Judge for yourself.
Run your own prompts against EXAONE 4.5 33B and Qwen3-235B-A22B-Instruct-2507 side-by-side, then vote on the output you prefer.
FAQ
Common questions about EXAONE 4.5 33B vs Qwen3-235B-A22B-Instruct-2507.