Model Comparison

LongCat-Flash-Thinking-2601 vs Qwen2.5 VL 32B Instruct

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

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

LongCat-Flash-Thinking-2601 outperforms in 1 benchmarks (GPQA), while Qwen2.5 VL 32B Instruct is better at 0 benchmarks.

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

Wed Apr 15 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
Wed Apr 15 2026 • llm-stats.com
Meituan
LongCat-Flash-Thinking-2601
Input tokens$0.30
Output tokens$1.20
Best providerMeituan
Alibaba Cloud / Qwen Team
Qwen2.5 VL 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

526.5B diff

LongCat-Flash-Thinking-2601 has 526.5B more parameters than Qwen2.5 VL 32B Instruct, making it 1571.6% larger.

Meituan
LongCat-Flash-Thinking-2601
560.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5 VL 32B Instruct
33.5Bparameters
560.0B
LongCat-Flash-Thinking-2601
33.5B
Qwen2.5 VL 32B Instruct

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).

Meituan
LongCat-Flash-Thinking-2601
Input128,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen2.5 VL 32B Instruct
Input- tokens
Output- tokens
Wed Apr 15 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen2.5 VL 32B Instruct supports multimodal inputs, whereas LongCat-Flash-Thinking-2601 does not.

Qwen2.5 VL 32B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

LongCat-Flash-Thinking-2601

Text
Images
Audio
Video

Qwen2.5 VL 32B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

LongCat-Flash-Thinking-2601 is licensed under MIT, while Qwen2.5 VL 32B Instruct uses Apache 2.0.

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

LongCat-Flash-Thinking-2601

MIT

Open weights

Qwen2.5 VL 32B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

LongCat-Flash-Thinking-2601 was released on 2026-01-14, while Qwen2.5 VL 32B Instruct was released on 2025-02-28.

LongCat-Flash-Thinking-2601 is 11 months newer than Qwen2.5 VL 32B Instruct.

LongCat-Flash-Thinking-2601

Jan 14, 2026

3 months ago

10mo newer
Qwen2.5 VL 32B Instruct

Feb 28, 2025

1.1 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 (80.5% vs 46.0%)
Alibaba Cloud / Qwen Team

Qwen2.5 VL 32B Instruct

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
Meituan
LongCat-Flash-Thinking-2601
Alibaba Cloud / Qwen Team
Qwen2.5 VL 32B Instruct

FAQ

Common questions about LongCat-Flash-Thinking-2601 vs Qwen2.5 VL 32B Instruct

LongCat-Flash-Thinking-2601 significantly outperforms across most benchmarks. LongCat-Flash-Thinking-2601 is made by Meituan and Qwen2.5 VL 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-Thinking-2601 scores AIME 2025: 99.6%, Tau2 Telecom: 99.3%, Tau2 Retail: 88.6%, LiveCodeBench: 82.8%, GPQA: 80.5%. Qwen2.5 VL 32B Instruct scores DocVQA: 94.8%, Android Control Low_EM: 93.3%, HumanEval: 91.5%, ScreenSpot: 88.5%, MBPP: 84.0%.
LongCat-Flash-Thinking-2601 supports 128K tokens and Qwen2.5 VL 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 multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
LongCat-Flash-Thinking-2601 is developed by Meituan and Qwen2.5 VL 32B Instruct is developed by Alibaba Cloud / Qwen Team.