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GLM-4.5-Air vs LongCat-Flash-Thinking

GLM-4.5-Air and LongCat-Flash-Thinking are closely matched at 24.4 and 28.6 on the LLM Stats Score.

Zhipu AI · Meituan · Updated for 2026

Which is better?

GLM-4.5-Air and LongCat-Flash-Thinking are closely matched on the overall LLM Stats Score at 24.4 and 28.6.

In the 7 individual benchmarks reported for both models, LongCat-Flash-Thinking wins 6; 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 GLM-4.5-Air

  • you are already invested in the Zhipu AI ecosystem

Choose LongCat-Flash-Thinking

  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 6 of 7 exact shared results
  • you want the most recent training data — it shipped Sep 2025

At a glance

The differences that matter most.

GLM-4.5-Air
Zhipu AI
LongCat-Flash-Thinking
Meituan
Core performance indexes
LLM Stats Score
24.4
#164
28.6
#133
Reasoning
23.8
#162
28.8
#124
Coding
11.4
#156
14.0
#135
Agents
5.9
#142
13.0
#95
Cost, coverage & limits
Benchmark wins
1 of 7
6 of 7
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

4 shared
Index
GLM-4.5-Air
LongCat-Flash-Thinking
Math
22.5#136
28.1#95
Tool use
20.2#59
15.8#88
Writing
19.6#20
18.3#28
Finance
26.6#43
27.4#39
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

14 reported for GLM-4.5-Air · 14 for LongCat-Flash-Thinking

7 shared

GLM-4.5-Air outperforms in 1 benchmarks (BFCL-v3), while LongCat-Flash-Thinking is better at 6 benchmarks (AIME 2024, GPQA, LiveCodeBench, MATH-500, MMLU-Pro, SWE-Bench Verified).

LongCat-Flash-Thinking significantly outperforms across most benchmarks.

Sun Sep 20 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

454.0B diff

LongCat-Flash-Thinking has 454.0B more parameters than GLM-4.5-Air, making it 428.3% larger.

Zhipu AI
GLM-4.5-Air
106.0Bparameters
Meituan
LongCat-Flash-Thinking
560.0Bparameters
106.0B
GLM-4.5-Air
560.0B
LongCat-Flash-Thinking

Context Window

Maximum input and output token capacity

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

Zhipu AI
GLM-4.5-Air
Input- tokens
Output- tokens
Meituan
LongCat-Flash-Thinking
Input128,000 tokens
Output128,000 tokens
Sun Sep 20 2026 • llm-stats.com

License

Usage and distribution terms

Both models are licensed under MIT.

Both models share the same licensing terms, providing consistent usage rights.

GLM-4.5-Air

MIT

Open weights

LongCat-Flash-Thinking

MIT

Open weights

Release Timeline

When each model was launched

GLM-4.5-Air was released on 2025-07-28, while LongCat-Flash-Thinking was released on 2025-09-22.

LongCat-Flash-Thinking is 2 months newer than GLM-4.5-Air.

GLM-4.5-Air

Jul 28, 2025

1.1 years ago

LongCat-Flash-Thinking

Sep 22, 2025

12 months ago

1mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against GLM-4.5-Air and LongCat-Flash-Thinking side-by-side, then vote on the output you prefer.

GLM-4.5-Air
✓ Preferred
LongCat-Flash-Thinking
Open in Playground

FAQ

Common questions about GLM-4.5-Air vs LongCat-Flash-Thinking.

Which is better, GLM-4.5-Air or LongCat-Flash-Thinking?

GLM-4.5-Air and LongCat-Flash-Thinking are closely matched on the LLM Stats Score at 24.4 and 28.6. GLM-4.5-Air is made by Zhipu AI and LongCat-Flash-Thinking is made by Meituan. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does GLM-4.5-Air compare to LongCat-Flash-Thinking in benchmarks?

GLM-4.5-Air scores MATH-500: 98.1%, AIME 2024: 89.4%, MMLU-Pro: 81.4%, TAU-bench Retail: 77.9%, BFCL-v3: 76.4%. LongCat-Flash-Thinking scores MATH-500: 99.2%, ZebraLogic: 95.5%, AIME 2024: 93.3%, AIME 2025: 90.6%, MMLU-Redux: 89.3%.

What are the context window sizes for GLM-4.5-Air and LongCat-Flash-Thinking?

GLM-4.5-Air supports an unknown number of tokens and LongCat-Flash-Thinking 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 GLM-4.5-Air and LongCat-Flash-Thinking?

Key differences include LLM Stats Score (24.4 vs 28.6). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-4.5-Air and LongCat-Flash-Thinking?

GLM-4.5-Air is developed by Zhipu AI and LongCat-Flash-Thinking is developed by Meituan.

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