LongCat-Flash-Thinking vs Qwen3 VL 30B A3B Instruct Comparison
Comparing LongCat-Flash-Thinking and Qwen3 VL 30B A3B Instruct across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
LongCat-Flash-Thinking outperforms in 5 benchmarks (AIME 2025, BFCL-v3, GPQA, MMLU-Pro, MMLU-Redux), while Qwen3 VL 30B A3B Instruct is better at 0 benchmarks.
LongCat-Flash-Thinking significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, LongCat-Flash-Thinking ($0.30/1M tokens) is 1.5x more expensive than Qwen3 VL 30B A3B Instruct ($0.20/1M tokens).
For output processing, LongCat-Flash-Thinking ($1.20/1M tokens) is 1.7x more expensive than Qwen3 VL 30B A3B Instruct ($0.70/1M tokens).
In conclusion, LongCat-Flash-Thinking is more expensive than Qwen3 VL 30B A3B Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
LongCat-Flash-Thinking has 529.0B more parameters than Qwen3 VL 30B A3B Instruct, making it 1706.5% larger.
Context Window
Maximum input and output token capacity
Qwen3 VL 30B A3B Instruct accepts 131,072 input tokens compared to LongCat-Flash-Thinking's 128,000 tokens. LongCat-Flash-Thinking can generate longer responses up to 128,000 tokens, while Qwen3 VL 30B A3B Instruct is limited to 32,768 tokens.
Input Capabilities
Supported data types and modalities
Qwen3 VL 30B A3B Instruct supports multimodal inputs, whereas LongCat-Flash-Thinking does not.
Qwen3 VL 30B A3B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
LongCat-Flash-Thinking
Qwen3 VL 30B A3B Instruct
License
Usage and distribution terms
LongCat-Flash-Thinking is licensed under MIT, while Qwen3 VL 30B A3B Instruct uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Both models were released on 2025-09-22.
They likely represent similar generations of model development.
Sep 22, 2025
5 months ago
Sep 22, 2025
5 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
LongCat-Flash-Thinking is available from Meituan. Qwen3 VL 30B A3B Instruct is available from Novita, DeepInfra. The availability of providers can affect quality of the model and reliability.
LongCat-Flash-Thinking
Qwen3 VL 30B A3B Instruct
Outputs Comparison
Key Takeaways
Qwen3 VL 30B A3B Instruct
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
| Feature | | |
|---|