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EXAONE 4.5 33B vs LongCat-Flash-Thinking-2601

LongCat-Flash-Thinking-2601 significantly outperforms across most benchmarks.

LG AI Research · Meituan · Updated for 2026

Which is better?

EXAONE 4.5 33B outperforms in 0 benchmarks, while LongCat-Flash-Thinking-2601 is better at 4 benchmarks (AIME 2025, Tau2 Airline, Tau2 Retail, Tau2 Telecom). LongCat-Flash-Thinking-2601 significantly outperforms across most benchmarks.

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

Choose EXAONE 4.5 33B

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

Choose LongCat-Flash-Thinking-2601

  • you want the strongest raw capability — it leads on 5 of 5 shared benchmarks
  • 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
LongCat-Flash-Thinking-2601
Meituan
Benchmark wins
0 of 5
5 of 5
Input price
— / M
$0.30 / M
Output price
— / M
$1.20 / M
Context window
—
128,000
Released
Apr 2026
Jan 2026
License
Proprietary
MIT

Performance Benchmarks

Comparative analysis across standard metrics

5 benchmarks

EXAONE 4.5 33B outperforms in 0 benchmarks, while LongCat-Flash-Thinking-2601 is better at 4 benchmarks (AIME 2025, Tau2 Airline, Tau2 Retail, Tau2 Telecom).

LongCat-Flash-Thinking-2601 significantly outperforms across most benchmarks.

Thu Aug 27 2026 • llm-stats.com

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

527.0B diff

LongCat-Flash-Thinking-2601 has 527.0B more parameters than EXAONE 4.5 33B, making it 1597.0% larger.

LG AI Research
EXAONE 4.5 33B
33.0Bparameters
Meituan
LongCat-Flash-Thinking-2601
560.0Bparameters
33.0B
EXAONE 4.5 33B
560.0B
LongCat-Flash-Thinking-2601

Context Window

Maximum input and output token capacity

Only LongCat-Flash-Thinking-2601 specifies input context (128,000 tokens). Only LongCat-Flash-Thinking-2601 specifies output context (128,000 tokens).

LG AI Research
EXAONE 4.5 33B
Input- tokens
Output- tokens
Meituan
LongCat-Flash-Thinking-2601
Input128,000 tokens
Output128,000 tokens
Thu Aug 27 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

EXAONE 4.5 33B supports multimodal inputs, whereas LongCat-Flash-Thinking-2601 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

Text
Images
Audio
Video

LongCat-Flash-Thinking-2601

Text
Images
Audio
Video

License

Usage and distribution terms

EXAONE 4.5 33B is licensed under a proprietary license, while LongCat-Flash-Thinking-2601 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

LongCat-Flash-Thinking-2601

MIT

Open weights

Release Timeline

When each model was launched

EXAONE 4.5 33B was released on 2026-04-09, while LongCat-Flash-Thinking-2601 was released on 2026-01-14.

EXAONE 4.5 33B is 3 months newer than LongCat-Flash-Thinking-2601.

EXAONE 4.5 33B

Apr 9, 2026

4 months ago

2mo newer
LongCat-Flash-Thinking-2601

Jan 14, 2026

7 months ago

Knowledge Cutoff

When training data ends

EXAONE 4.5 33B has a documented knowledge cutoff of 2024-12-01, while LongCat-Flash-Thinking-2601'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 LongCat-Flash-Thinking-2601's cutoff date.

EXAONE 4.5 33B

Dec 2024

LongCat-Flash-Thinking-2601

—

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against EXAONE 4.5 33B and LongCat-Flash-Thinking-2601 side-by-side, then vote on the output you prefer.

EXAONE 4.5 33B
✓ Preferred
LongCat-Flash-Thinking-2601
Open in Playground

FAQ

Common questions about EXAONE 4.5 33B vs LongCat-Flash-Thinking-2601.

Which is better, EXAONE 4.5 33B or LongCat-Flash-Thinking-2601?

LongCat-Flash-Thinking-2601 significantly outperforms across most benchmarks. EXAONE 4.5 33B is made by LG AI Research and LongCat-Flash-Thinking-2601 is made by Meituan. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does EXAONE 4.5 33B compare to LongCat-Flash-Thinking-2601 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%. LongCat-Flash-Thinking-2601 scores AIME 2025: 99.6%, Tau2 Telecom: 99.3%, Tau2 Retail: 88.6%, LiveCodeBench: 82.8%, GPQA: 80.5%.

What are the context window sizes for EXAONE 4.5 33B and LongCat-Flash-Thinking-2601?

EXAONE 4.5 33B supports an unknown number of tokens and LongCat-Flash-Thinking-2601 supports 128K 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 LongCat-Flash-Thinking-2601?

Key differences include multimodal support (yes vs no), licensing (Proprietary vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes EXAONE 4.5 33B and LongCat-Flash-Thinking-2601?

EXAONE 4.5 33B is developed by LG AI Research and LongCat-Flash-Thinking-2601 is developed by Meituan.

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