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EXAONE 4.5 33B vs o4-mini

EXAONE 4.5 33B and o4-mini are closely matched at 26.0 and 27.5 on the LLM Stats Score.

LG AI Research · OpenAI · Updated for 2026

Which is better?

EXAONE 4.5 33B and o4-mini are closely matched on the overall LLM Stats Score at 26.0 and 27.5.

In the 3 individual benchmarks reported for both models, o4-mini wins 2; 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 want the most recent training data — it shipped Apr 2026

Choose o4-mini

  • you value its reported benchmark strengths — it wins 2 of 3 exact shared results

At a glance

The differences that matter most.

Core performance indexes
26.0
#151
27.5
#142
26.6
#144
27.5
#135
Cost, coverage & limits
Benchmark wins
1 of 3
2 of 3
Input price
— / M
$1.10 / M
Output price
— / M
$4.40 / M
Context window
200,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

5 shared
Index
EXAONE 4.5 33B
o4-mini
28.4#93
27.6#97
13.4#95
15.8#89
10.6#122
11.6#110
14.9#45
12.4#62
16.3#80
21.8#62
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

15 reported for EXAONE 4.5 33B · 14 for o4-mini

3 shared

EXAONE 4.5 33B outperforms in 1 benchmarks (AIME 2025), while o4-mini is better at 2 benchmarks (GPQA, MMMU).

o4-mini shows notably better performance in the majority of benchmarks.

Sat Sep 12 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only o4-mini specifies input context (200,000 tokens). Only o4-mini specifies output context (100,000 tokens).

LG AI Research
EXAONE 4.5 33B
Input- tokens
Output- tokens
OpenAI
o4-mini
Input200,000 tokens
Output100,000 tokens
Sat Sep 12 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both EXAONE 4.5 33B and o4-mini 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

o4-mini

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

o4-mini

Proprietary

Closed source

Release Timeline

When each model was launched

EXAONE 4.5 33B was released on 2026-04-09, while o4-mini was released on 2025-04-16.

EXAONE 4.5 33B is 12 months newer than o4-mini.

EXAONE 4.5 33B

Apr 9, 2026

5 months ago

11mo newer
o4-mini

Apr 16, 2025

1.4 years ago

Knowledge Cutoff

When training data ends

EXAONE 4.5 33B has a knowledge cutoff of 2024-12-01, while o4-mini has a cutoff of 2024-05-31.

EXAONE 4.5 33B has more recent training data (up to 2024-12-01), making it potentially better informed about events through that date compared to o4-mini (2024-05-31).

EXAONE 4.5 33B

Dec 2024

7 mo newer
o4-mini

May 2024

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against EXAONE 4.5 33B and o4-mini side-by-side, then vote on the output you prefer.

EXAONE 4.5 33B
✓ Preferred
o4-mini
Open in Playground

FAQ

Common questions about EXAONE 4.5 33B vs o4-mini.

Which is better, EXAONE 4.5 33B or o4-mini?

EXAONE 4.5 33B and o4-mini are closely matched on the LLM Stats Score at 26.0 and 27.5. EXAONE 4.5 33B is made by LG AI Research and o4-mini is made by OpenAI. 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 o4-mini 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%. o4-mini scores AIME 2024: 93.4%, AIME 2025: 92.7%, MathVista: 84.3%, MMMU: 81.6%, GPQA: 81.4%.

What are the context window sizes for EXAONE 4.5 33B and o4-mini?

EXAONE 4.5 33B supports an unknown number of tokens and o4-mini supports 200K 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 o4-mini?

Key differences include LLM Stats Score (26.0 vs 27.5). See the full comparison above for benchmark-by-benchmark results.

Who makes EXAONE 4.5 33B and o4-mini?

EXAONE 4.5 33B is developed by LG AI Research and o4-mini is developed by OpenAI.