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EXAONE 4.5 33B vs GLM-5.3-Flash

Comparing EXAONE 4.5 33B and GLM-5.3-Flash across benchmarks, pricing, and capabilities.

LG AI Research · Zhipu AI · Updated for 2026

Which is better?

EXAONE 4.5 33B and GLM-5.3-Flash trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

Based on current benchmark, pricing, and model metadata for 2026.

Choose EXAONE 4.5 33B

  • you are already invested in the LG AI Research ecosystem

Choose GLM-5.3-Flash

  • 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.

EXAONE 4.5 33B
LG AI Research
GLM-5.3-Flash
Zhipu AI
Benchmark wins
—
—
Input price
— / M
$0.15 / M
Output price
— / M
$0.50 / M
Context window
—
1,048,576
Released
Apr 2026
Aug 2026
License
Proprietary
MIT

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

EXAONE 4.5 33B and GLM-5.3-Flashdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

287.0B diff

GLM-5.3-Flash has 287.0B more parameters than EXAONE 4.5 33B, making it 869.7% larger.

LG AI Research
EXAONE 4.5 33B
33.0Bparameters
Zhipu AI
GLM-5.3-Flash
320.0Bparameters
33.0B
EXAONE 4.5 33B
320.0B
GLM-5.3-Flash

Context Window

Maximum input and output token capacity

Only GLM-5.3-Flash specifies input context (1,048,576 tokens). Only GLM-5.3-Flash specifies output context (131,072 tokens).

LG AI Research
EXAONE 4.5 33B
Input- tokens
Output- tokens
Zhipu AI
GLM-5.3-Flash
Input1,048,576 tokens
Output131,072 tokens
Thu Aug 27 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both EXAONE 4.5 33B and GLM-5.3-Flash 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

GLM-5.3-Flash

Text
Images
Audio
Video

License

Usage and distribution terms

EXAONE 4.5 33B is licensed under a proprietary license, while GLM-5.3-Flash uses MIT.

License differences may affect how you can use these models in commercial or open-source projects.

EXAONE 4.5 33B

Proprietary

Closed source

GLM-5.3-Flash

MIT

Open weights

Release Timeline

When each model was launched

EXAONE 4.5 33B was released on 2026-04-09, while GLM-5.3-Flash was released on 2026-08-26.

GLM-5.3-Flash is 5 months newer than EXAONE 4.5 33B.

EXAONE 4.5 33B

Apr 9, 2026

4 months ago

GLM-5.3-Flash

Aug 26, 2026

0 days ago

4mo newer

Knowledge Cutoff

When training data ends

EXAONE 4.5 33B has a documented knowledge cutoff of 2024-12-01, while GLM-5.3-Flash'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 GLM-5.3-Flash's cutoff date.

EXAONE 4.5 33B

Dec 2024

GLM-5.3-Flash

—

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against EXAONE 4.5 33B and GLM-5.3-Flash side-by-side, then vote on the output you prefer.

EXAONE 4.5 33B
✓ Preferred
GLM-5.3-Flash
Open in Playground

FAQ

Common questions about EXAONE 4.5 33B vs GLM-5.3-Flash.

Which is better, EXAONE 4.5 33B or GLM-5.3-Flash?

EXAONE 4.5 33B (LG AI Research) and GLM-5.3-Flash (Zhipu AI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does EXAONE 4.5 33B compare to GLM-5.3-Flash 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%. GLM-5.3-Flash scores CharXiv-R: 89.4%, Terminal-Bench 2.1: 84.3%, MMVU: 80.5%, Toolathlon: 78.4%, Chartography: 78.0%.

What are the context window sizes for EXAONE 4.5 33B and GLM-5.3-Flash?

EXAONE 4.5 33B supports an unknown number of tokens and GLM-5.3-Flash supports 1.0M 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 GLM-5.3-Flash?

Key differences include licensing (Proprietary vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes EXAONE 4.5 33B and GLM-5.3-Flash?

EXAONE 4.5 33B is developed by LG AI Research and GLM-5.3-Flash is developed by Zhipu AI.

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