Model Comparison

LongCat-Flash-Chat vs Qwen2.5 32B Instruct

LongCat-Flash-Chat significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

LongCat-Flash-Chat outperforms in 4 benchmarks (GPQA, HumanEval, MMLU, MMLU-Pro), while Qwen2.5 32B Instruct is better at 0 benchmarks.

LongCat-Flash-Chat significantly outperforms across most benchmarks.

Tue Apr 14 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
Tue Apr 14 2026 • llm-stats.com
Meituan
LongCat-Flash-Chat
Input tokens$0.30
Output tokens$1.20
Best providerMeituan
Alibaba Cloud / Qwen Team
Qwen2.5 32B 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

527.5B diff

LongCat-Flash-Chat has 527.5B more parameters than Qwen2.5 32B Instruct, making it 1623.1% larger.

Meituan
LongCat-Flash-Chat
560.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5 32B Instruct
32.5Bparameters
560.0B
LongCat-Flash-Chat
32.5B
Qwen2.5 32B Instruct

Context Window

Maximum input and output token capacity

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

Meituan
LongCat-Flash-Chat
Input128,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen2.5 32B Instruct
Input- tokens
Output- tokens
Tue Apr 14 2026 • llm-stats.com

License

Usage and distribution terms

LongCat-Flash-Chat is licensed under MIT, while Qwen2.5 32B Instruct uses Apache 2.0.

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

LongCat-Flash-Chat

MIT

Open weights

Qwen2.5 32B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

LongCat-Flash-Chat was released on 2025-08-29, while Qwen2.5 32B Instruct was released on 2024-09-19.

LongCat-Flash-Chat is 11 months newer than Qwen2.5 32B Instruct.

LongCat-Flash-Chat

Aug 29, 2025

7 months ago

11mo newer
Qwen2.5 32B Instruct

Sep 19, 2024

1.6 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 (73.2% vs 49.5%)
Higher HumanEval score (88.4% vs 88.4%)
Higher MMLU score (89.7% vs 83.3%)
Higher MMLU-Pro score (82.7% vs 69.0%)
Alibaba Cloud / Qwen Team

Qwen2.5 32B Instruct

View details

Alibaba Cloud / Qwen Team

Detailed Comparison

AI Model Comparison Table
Feature
Meituan
LongCat-Flash-Chat
Alibaba Cloud / Qwen Team
Qwen2.5 32B Instruct

FAQ

Common questions about LongCat-Flash-Chat vs Qwen2.5 32B Instruct

LongCat-Flash-Chat significantly outperforms across most benchmarks. LongCat-Flash-Chat is made by Meituan and Qwen2.5 32B 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-Chat scores MATH-500: 96.4%, MMLU: 89.7%, IFEval: 89.6%, ZebraLogic: 89.3%, HumanEval: 88.4%. Qwen2.5 32B Instruct scores GSM8k: 95.9%, HumanEval: 88.4%, HellaSwag: 85.2%, BBH: 84.5%, MBPP: 84.0%.
LongCat-Flash-Chat supports 128K tokens and Qwen2.5 32B 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 Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
LongCat-Flash-Chat is developed by Meituan and Qwen2.5 32B Instruct is developed by Alibaba Cloud / Qwen Team.