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EXAONE 4.5 33B vs Qwen3 VL 235B A22B Instruct

EXAONE 4.5 33B and Qwen3 VL 235B A22B Instruct are closely matched at 26.0 and 24.7 on the LLM Stats Score.

LG AI Research · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

EXAONE 4.5 33B and Qwen3 VL 235B A22B Instruct are closely matched on the overall LLM Stats Score at 26.0 and 24.7.

In the 8 individual benchmarks reported for both models, EXAONE 4.5 33B wins 6; 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

  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 6 of 8 exact shared results
  • 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.

EXAONE 4.5 33B
LG AI Research
Qwen3 VL 235B A22B Instruct
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
26.0
#160
24.7
#170
Reasoning
26.6
#153
22.5
#178
Cost, coverage & limits
Benchmark wins
6 of 8
2 of 8
Input price
— / M
$0.20 / M
Output price
— / M
$0.88 / M
Context window
—
262,144

Capability indexes

Additional strengths measured across groups of related public benchmarks

4 shared
Index
EXAONE 4.5 33B
Qwen3 VL 235B A22B Instruct
Math
28.4#95
23.8#126
Vision
13.4#102
17.9#88
Writing
14.9#45
16.3#39
Multimodal
16.3#87
20.6#72
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

15 reported for EXAONE 4.5 33B · 50 for Qwen3 VL 235B A22B Instruct

8 shared

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.

Mon Oct 05 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

203.0B diff

Qwen3 VL 235B A22B Instruct has 203.0B more parameters than EXAONE 4.5 33B, making it 615.2% larger.

LG AI Research
EXAONE 4.5 33B
33.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Instruct
236.0Bparameters
33.0B
EXAONE 4.5 33B
236.0B
Qwen3 VL 235B A22B Instruct

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).

LG AI Research
EXAONE 4.5 33B
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Instruct
Input262,144 tokens
Output262,144 tokens
Mon Oct 05 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

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

Text
Images
Audio
Video

Qwen3 VL 235B A22B Instruct

Text
Images
Audio
Video

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.

EXAONE 4.5 33B

Proprietary

Closed source

Qwen3 VL 235B A22B Instruct

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.

EXAONE 4.5 33B

Apr 9, 2026

5 months ago

6mo newer
Qwen3 VL 235B A22B Instruct

Sep 22, 2025

1.0 years 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.

EXAONE 4.5 33B

Dec 2024

Qwen3 VL 235B A22B Instruct

—

Outputs Comparison

Notice missing or incorrect data?

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.

EXAONE 4.5 33B
✓ Preferred
Qwen3 VL 235B A22B Instruct
Open in Playground

FAQ

Common questions about EXAONE 4.5 33B vs Qwen3 VL 235B A22B Instruct.

Which is better, EXAONE 4.5 33B or Qwen3 VL 235B A22B Instruct?

EXAONE 4.5 33B and Qwen3 VL 235B A22B Instruct are closely matched on the LLM Stats Score at 26.0 and 24.7. EXAONE 4.5 33B is made by LG AI Research and Qwen3 VL 235B A22B Instruct is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does EXAONE 4.5 33B compare to Qwen3 VL 235B A22B Instruct in benchmarks?

EXAONE 4.5 33B scores AIME 2025: 92.9%, AIME 2026: 92.6%, IFEval: 89.6%, AI2D: 89.0%, MathVista-Mini: 85.0%. Qwen3 VL 235B A22B Instruct scores DocVQAtest: 97.1%, ScreenSpot: 95.4%, MMLU-Redux: 92.2%, OCRBench: 92.0%, MMBench-V1.1: 89.9%.

What are the context window sizes for EXAONE 4.5 33B and Qwen3 VL 235B A22B Instruct?

EXAONE 4.5 33B supports an unknown number of tokens and Qwen3 VL 235B A22B Instruct supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between EXAONE 4.5 33B and Qwen3 VL 235B A22B Instruct?

Key differences include LLM Stats Score (26.0 vs 24.7), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes EXAONE 4.5 33B and Qwen3 VL 235B A22B Instruct?

EXAONE 4.5 33B is developed by LG AI Research and Qwen3 VL 235B A22B Instruct is developed by Alibaba Cloud / Qwen Team.

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