Model Comparison
LongCat-Flash-Thinking vs Qwen3 MaxWhich is better in 2026?
LongCat-Flash-Thinking shows notably better performance in the majority of benchmarks. LongCat-Flash-Thinking is 3.1x cheaper per token.
Verdict: LongCat-Flash-Thinking vs Qwen3 Max — which is better?
LongCat-Flash-Thinking (by Meituan) and Qwen3 Max (by Alibaba Cloud / Qwen Team) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
LongCat-Flash-Thinking outperforms in 2 benchmarks (AIME 2025, GPQA), while Qwen3 Max is better at 1 benchmark (SWE-Bench Verified). LongCat-Flash-Thinking shows notably better performance in the majority of benchmarks.
On price, LongCat-Flash-Thinking is roughly 3.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3 Max also accepts a larger context window (256,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose LongCat-Flash-Thinking if…
- you want the strongest raw capability — it leads on 2 of 3 shared benchmarks
- cost matters — it's about 3.1x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Qwen3 Max if…
- you process long inputs — it offers a 256,000 token context window
- you want the most recent training data — it shipped Dec 2025
Performance Benchmarks
Comparative analysis across standard metrics
LongCat-Flash-Thinking outperforms in 2 benchmarks (AIME 2025, GPQA), while Qwen3 Max is better at 1 benchmark (SWE-Bench Verified).
LongCat-Flash-Thinking shows notably better performance in the majority of benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, LongCat-Flash-Thinking ($0.30/1M tokens) is 1.7x cheaper than Qwen3 Max ($0.50/1M tokens).
For output processing, LongCat-Flash-Thinking ($1.20/1M tokens) is 4.2x cheaper than Qwen3 Max ($5.00/1M tokens).
In conclusion, Qwen3 Max is more expensive than LongCat-Flash-Thinking.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Qwen3 Max has 440.0B more parameters than LongCat-Flash-Thinking, making it 78.6% larger.
Context Window
Maximum input and output token capacity
Qwen3 Max accepts 256,000 input tokens compared to LongCat-Flash-Thinking's 128,000 tokens. Qwen3 Max can generate longer responses up to 131,072 tokens, while LongCat-Flash-Thinking is limited to 128,000 tokens.
License
Usage and distribution terms
LongCat-Flash-Thinking is licensed under MIT, while Qwen3 Max uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
LongCat-Flash-Thinking was released on 2025-09-22, while Qwen3 Max was released on 2025-12-15.
Qwen3 Max is 3 months newer than LongCat-Flash-Thinking.
Sep 22, 2025
8 months ago
Dec 15, 2025
5 months ago
2mo newerKnowledge 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 Max is available from Novita.
LongCat-Flash-Thinking
Qwen3 Max
Outputs Comparison
Key Takeaways
Qwen3 Max
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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FAQ
Common questions about LongCat-Flash-Thinking vs Qwen3 Max.