LongCat-Flash-Thinking-2601 vs QwQ-32B-Preview
LongCat-Flash-Thinking-2601 leads the LLM Stats Score 35.7 to 9.2. QwQ-32B-Preview is 3.2x cheaper per token.
Meituan · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
LongCat-Flash-Thinking-2601 leads the overall LLM Stats Score 35.7 to 9.2, ranking #78 overall.
In the 2 individual benchmarks reported for both models, LongCat-Flash-Thinking-2601 wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, QwQ-32B-Preview is roughly 3.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
LongCat-Flash-Thinking-2601 also accepts a larger context window (128,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose LongCat-Flash-Thinking-2601
- overall performance matters — it scores 35.7 and ranks #78 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- you process long inputs — it offers a 128,000 token context window
- you want the most recent training data — it shipped Jan 2026
Choose QwQ-32B-Preview
- cost matters — it's about 3.2x cheaper per token
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
11 reported for LongCat-Flash-Thinking-2601 · 4 for QwQ-32B-Preview
LongCat-Flash-Thinking-2601 outperforms in 2 benchmarks (GPQA, LiveCodeBench), while QwQ-32B-Preview is better at 0 benchmarks.
LongCat-Flash-Thinking-2601 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, LongCat-Flash-Thinking-2601 ($0.30/1M tokens) is 2.0x more expensive than QwQ-32B-Preview ($0.15/1M tokens).
For output processing, LongCat-Flash-Thinking-2601 ($1.20/1M tokens) is 6.0x more expensive than QwQ-32B-Preview ($0.20/1M tokens).
In conclusion, LongCat-Flash-Thinking-2601 is more expensive than QwQ-32B-Preview.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
LongCat-Flash-Thinking-2601 has 527.5B more parameters than QwQ-32B-Preview, making it 1623.1% larger.
Context Window
Maximum input and output token capacity
LongCat-Flash-Thinking-2601 accepts 128,000 input tokens compared to QwQ-32B-Preview's 32,768 tokens. LongCat-Flash-Thinking-2601 can generate longer responses up to 128,000 tokens, while QwQ-32B-Preview is limited to 32,768 tokens.
License
Usage and distribution terms
LongCat-Flash-Thinking-2601 is licensed under MIT, while QwQ-32B-Preview 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
LongCat-Flash-Thinking-2601 was released on 2026-01-14, while QwQ-32B-Preview was released on 2024-11-28.
LongCat-Flash-Thinking-2601 is 14 months newer than QwQ-32B-Preview.
Jan 14, 2026
7 months ago
1.1yr newerNov 28, 2024
1.8 years ago
Knowledge Cutoff
When training data ends
QwQ-32B-Preview has a documented knowledge cutoff of 2024-11-28, while LongCat-Flash-Thinking-2601's cutoff date is not specified.
We can confirm QwQ-32B-Preview's training data extends to 2024-11-28, but cannot make a direct comparison without LongCat-Flash-Thinking-2601's cutoff date.
—
Nov 2024
Provider Availability
LongCat-Flash-Thinking-2601 is available from Meituan. QwQ-32B-Preview is available from DeepInfra, Hyperbolic, Fireworks, Together.
LongCat-Flash-Thinking-2601
QwQ-32B-Preview
Outputs Comparison
Judge for yourself.
Run your own prompts against LongCat-Flash-Thinking-2601 and QwQ-32B-Preview side-by-side, then vote on the output you prefer.
FAQ
Common questions about LongCat-Flash-Thinking-2601 vs QwQ-32B-Preview.