LongCat-Flash-Thinking vs Qwen3.8 Max
Qwen3.8 Max significantly outperforms across most benchmarks. LongCat-Flash-Thinking is 4.7x cheaper per token.
Meituan · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
LongCat-Flash-Thinking outperforms in 0 benchmarks, while Qwen3.8 Max is better at 1 benchmark (GPQA). Qwen3.8 Max significantly outperforms across most benchmarks.
On price, LongCat-Flash-Thinking is roughly 4.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3.8 Max also accepts a larger context window (256,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current benchmark, pricing, and model metadata for 2026.
Choose LongCat-Flash-Thinking
- cost matters — it's about 4.7x cheaper per token
Choose Qwen3.8 Max
- you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
- you process long inputs — it offers a 256,000 token context window
- you want the most recent training data — it shipped Aug 2026
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
LongCat-Flash-Thinking outperforms in 0 benchmarks, while Qwen3.8 Max is better at 1 benchmark (GPQA).
Qwen3.8 Max significantly outperforms across most benchmarks.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, LongCat-Flash-Thinking ($0.30/1M tokens) is 5.5x cheaper than Qwen3.8 Max ($1.65/1M tokens).
For output processing, LongCat-Flash-Thinking ($1.20/1M tokens) is 4.1x cheaper than Qwen3.8 Max ($4.95/1M tokens).
In conclusion, Qwen3.8 Max is more expensive than LongCat-Flash-Thinking.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Qwen3.8 Max has 1840.0B more parameters than LongCat-Flash-Thinking, making it 328.6% larger.
Context Window
Maximum input and output token capacity
Qwen3.8 Max accepts 256,000 input tokens compared to LongCat-Flash-Thinking's 128,000 tokens. Qwen3.8 Max can generate longer responses up to 131,072 tokens, while LongCat-Flash-Thinking is limited to 128,000 tokens.
Input Capabilities
Supported data types and modalities
Qwen3.8 Max supports multimodal inputs, whereas LongCat-Flash-Thinking does not.
Qwen3.8 Max can handle both text and other forms of data like images, making it suitable for multimodal applications.
LongCat-Flash-Thinking
Qwen3.8 Max
License
Usage and distribution terms
LongCat-Flash-Thinking is licensed under MIT, while Qwen3.8 Max uses Qwen3.8-Max License.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Qwen3.8-Max License
Open weights
Release Timeline
When each model was launched
LongCat-Flash-Thinking was released on 2025-09-22, while Qwen3.8 Max was released on 2026-08-02.
Qwen3.8 Max is 10 months newer than LongCat-Flash-Thinking.
Sep 22, 2025
11 months ago
Aug 2, 2026
3 weeks ago
10mo 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. Qwen3.8 Max is available from DeepInfra, Fireworks, Novita, Together.
LongCat-Flash-Thinking
Qwen3.8 Max
Outputs Comparison
Judge for yourself.
Run your own prompts against LongCat-Flash-Thinking and Qwen3.8 Max side-by-side, then vote on the output you prefer.
FAQ
Common questions about LongCat-Flash-Thinking vs Qwen3.8 Max.