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

LongCat-Flash-Thinking-2601 leads the LLM Stats Score 35.3 to 26.0.

LG AI Research · Meituan · Updated for 2026

Which is better?

LongCat-Flash-Thinking-2601 leads the overall LLM Stats Score 35.3 to 26.0, ranking #93 overall.

In the 5 individual benchmarks reported for both models, LongCat-Flash-Thinking-2601 wins 5; 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 LongCat-Flash-Thinking-2601

  • overall performance matters — it scores 35.3 and ranks #93 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 5 of 5 exact shared results
  • 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
Core performance indexes
LLM Stats Score
26.0
#160
35.3
#93
Reasoning
26.6
#153
35.5
#87
Cost, coverage & limits
Benchmark wins
0 of 5
5 of 5
Input price
— / M
$0.30 / M
Output price
— / M
$1.20 / M
Context window
—
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
EXAONE 4.5 33B
LongCat-Flash-Thinking-2601
Math
28.4#95
30.5#76
Tool use
10.4#130
24.1#36
Writing
14.9#45
30.1#2
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

15 reported for EXAONE 4.5 33B · 11 for LongCat-Flash-Thinking-2601

5 shared

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.

Wed Oct 07 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground 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
Wed Oct 07 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

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

6 months ago

2mo newer
LongCat-Flash-Thinking-2601

Jan 14, 2026

8 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?

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 leads the LLM Stats Score 35.3 to 26.0. 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 capability indexes, individual benchmarks, pricing, and limits 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 LLM Stats Score (26.0 vs 35.3), 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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