Model Comparison

LongCat-Flash-Thinking vs Qwen2 72B Instruct

LongCat-Flash-Thinking significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

LongCat-Flash-Thinking outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Qwen2 72B Instruct is better at 0 benchmarks.

LongCat-Flash-Thinking significantly outperforms across most benchmarks.

Sat Apr 18 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Sat Apr 18 2026 • llm-stats.com
Meituan
LongCat-Flash-Thinking
Input tokens$0.30
Output tokens$1.20
Best providerMeituan
Alibaba Cloud / Qwen Team
Qwen2 72B Instruct
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

488.0B diff

LongCat-Flash-Thinking has 488.0B more parameters than Qwen2 72B Instruct, making it 677.8% larger.

Meituan
LongCat-Flash-Thinking
560.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2 72B Instruct
72.0Bparameters
560.0B
LongCat-Flash-Thinking
72.0B
Qwen2 72B Instruct

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).

Meituan
LongCat-Flash-Thinking
Input128,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen2 72B Instruct
Input- tokens
Output- tokens
Sat Apr 18 2026 • llm-stats.com

License

Usage and distribution terms

LongCat-Flash-Thinking is licensed under MIT, while Qwen2 72B Instruct uses tongyi-qianwen.

License differences may affect how you can use these models in commercial or open-source projects.

LongCat-Flash-Thinking

MIT

Open weights

Qwen2 72B Instruct

tongyi-qianwen

Open weights

Release Timeline

When each model was launched

LongCat-Flash-Thinking was released on 2025-09-22, while Qwen2 72B Instruct was released on 2024-07-23.

LongCat-Flash-Thinking is 14 months newer than Qwen2 72B Instruct.

LongCat-Flash-Thinking

Sep 22, 2025

6 months ago

1.2yr newer
Qwen2 72B Instruct

Jul 23, 2024

1.7 years ago

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

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Key Takeaways

Meituan
Larger context window (128,000 tokens)
Higher GPQA score (81.5% vs 42.4%)
Higher MMLU-Pro score (82.6% vs 64.4%)
Alibaba Cloud / Qwen Team

Qwen2 72B Instruct

View details

Alibaba Cloud / Qwen Team

Detailed Comparison

AI Model Comparison Table
Feature
Meituan
LongCat-Flash-Thinking
Alibaba Cloud / Qwen Team
Qwen2 72B Instruct

FAQ

Common questions about LongCat-Flash-Thinking vs Qwen2 72B Instruct

LongCat-Flash-Thinking significantly outperforms across most benchmarks. LongCat-Flash-Thinking is made by Meituan and Qwen2 72B Instruct is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
LongCat-Flash-Thinking scores MATH-500: 99.2%, ZebraLogic: 95.5%, AIME 2024: 93.3%, AIME 2025: 90.6%, MMLU-Redux: 89.3%. Qwen2 72B Instruct scores GSM8k: 91.1%, CMMLU: 90.1%, HellaSwag: 87.6%, HumanEval: 86.0%, Winogrande: 85.1%.
LongCat-Flash-Thinking supports 128K tokens and Qwen2 72B Instruct supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (MIT vs tongyi-qianwen). See the full comparison above for benchmark-by-benchmark results.
LongCat-Flash-Thinking is developed by Meituan and Qwen2 72B Instruct is developed by Alibaba Cloud / Qwen Team.