Qwen3.5-397B-A17B vs LongCat-Flash-Lite Comparison
Comparing Qwen3.5-397B-A17B and LongCat-Flash-Lite across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
Qwen3.5-397B-A17B outperforms in 4 benchmarks (GPQA, MMLU-Pro, SWE-bench Multilingual, SWE-Bench Verified), while LongCat-Flash-Lite is better at 0 benchmarks.
Qwen3.5-397B-A17B significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
Cost data unavailable.
Model Size
Parameter count comparison
Qwen3.5-397B-A17B has 328.5B more parameters than LongCat-Flash-Lite, making it 479.6% larger.
Context Window
Maximum input and output token capacity
Only Qwen3.5-397B-A17B specifies input context (262,144 tokens). Only Qwen3.5-397B-A17B specifies output context (64,000 tokens).
Input Capabilities
Supported data types and modalities
Qwen3.5-397B-A17B supports multimodal inputs, whereas LongCat-Flash-Lite does not.
Qwen3.5-397B-A17B can handle both text and other forms of data like images, making it suitable for multimodal applications.
Qwen3.5-397B-A17B
LongCat-Flash-Lite
License
Usage and distribution terms
Qwen3.5-397B-A17B is licensed under Apache 2.0, while LongCat-Flash-Lite uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
MIT
Open weights
Release Timeline
When each model was launched
Qwen3.5-397B-A17B was released on 2026-02-16, while LongCat-Flash-Lite was released on 2026-02-05.
Qwen3.5-397B-A17B is 0 month newer than LongCat-Flash-Lite.
Feb 16, 2026
4 weeks ago
1w newerFeb 5, 2026
1 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Key Takeaways
Qwen3.5-397B-A17B
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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