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EXAONE 4.5 33B vs Parse

Comparing EXAONE 4.5 33B and Parse across benchmarks, pricing, and capabilities.

LG AI Research · Cohere · Updated for 2026

Which is better?

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

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 Parse

  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

Benchmark wins
Input price
— / M
— / M
Output price
— / M
— / M
Context window
8,192

Individual benchmarks

15 reported for EXAONE 4.5 33B · 1 for Parse

No common benchmarks found

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

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

30.7B diff

EXAONE 4.5 33B has 30.7B more parameters than Parse, making it 1334.8% larger.

LG AI Research
EXAONE 4.5 33B
33.0Bparameters
Cohere
Parse
2.3Bparameters
33.0B
EXAONE 4.5 33B
2.3B
Parse

Context Window

Maximum input and output token capacity

Only Parse specifies input context (8,192 tokens).

LG AI Research
EXAONE 4.5 33B
Input- tokens
Output- tokens
Cohere
Parse
Input8,192 tokens
Output- tokens
Sun Sep 06 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both EXAONE 4.5 33B and Parse 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

Parse

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under proprietary licenses.

Both models have usage restrictions defined by their respective organizations.

EXAONE 4.5 33B

Proprietary

Closed source

Parse

Proprietary

Closed source

Release Timeline

When each model was launched

EXAONE 4.5 33B was released on 2026-04-09, while Parse was released on 2026-08-27.

Parse is 5 months newer than EXAONE 4.5 33B.

EXAONE 4.5 33B

Apr 9, 2026

4 months ago

Parse

Aug 27, 2026

1 weeks ago

4mo newer

Knowledge Cutoff

When training data ends

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

EXAONE 4.5 33B

Dec 2024

Parse

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

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

EXAONE 4.5 33B
✓ Preferred
Parse
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FAQ

Common questions about EXAONE 4.5 33B vs Parse.

Which is better, EXAONE 4.5 33B or Parse?

EXAONE 4.5 33B (LG AI Research) and Parse (Cohere) 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 Parse 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%. Parse scores ParseBench: 79.2%.

What are the context window sizes for EXAONE 4.5 33B and Parse?

EXAONE 4.5 33B supports an unknown number of tokens and Parse supports 8K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

Who makes EXAONE 4.5 33B and Parse?

EXAONE 4.5 33B is developed by LG AI Research and Parse is developed by Cohere.