LongCat-Flash-Chat vs QwQ-32B-Preview
LongCat-Flash-Chat leads the LLM Stats Score 19.9 to 9.1. QwQ-32B-Preview is 3.2x cheaper per token.
Meituan · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
LongCat-Flash-Chat leads the overall LLM Stats Score 19.9 to 9.1, ranking #196 overall.
In the 3 individual benchmarks reported for both models, LongCat-Flash-Chat 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-Chat 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-Chat
- overall performance matters — it scores 19.9 and ranks #196 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 3 exact shared results
- you process long inputs — it offers a 128,000 token context window
- you want the most recent training data — it shipped Aug 2025
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
16 reported for LongCat-Flash-Chat · 4 for QwQ-32B-Preview
LongCat-Flash-Chat outperforms in 2 benchmarks (GPQA, MATH-500), while QwQ-32B-Preview is better at 1 benchmark (LiveCodeBench).
LongCat-Flash-Chat shows notably better performance in the majority of benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, LongCat-Flash-Chat ($0.30/1M tokens) is 2.0x more expensive than QwQ-32B-Preview ($0.15/1M tokens).
For output processing, LongCat-Flash-Chat ($1.20/1M tokens) is 6.0x more expensive than QwQ-32B-Preview ($0.20/1M tokens).
In conclusion, LongCat-Flash-Chat is more expensive than QwQ-32B-Preview.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
LongCat-Flash-Chat has 527.5B more parameters than QwQ-32B-Preview, making it 1623.1% larger.
Context Window
Maximum input and output token capacity
LongCat-Flash-Chat accepts 128,000 input tokens compared to QwQ-32B-Preview's 32,768 tokens. LongCat-Flash-Chat 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-Chat 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-Chat was released on 2025-08-29, while QwQ-32B-Preview was released on 2024-11-28.
LongCat-Flash-Chat is 9 months newer than QwQ-32B-Preview.
Aug 29, 2025
1.0 years ago
9mo 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-Chat'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-Chat's cutoff date.
—
Nov 2024
Provider Availability
LongCat-Flash-Chat is available from Meituan. QwQ-32B-Preview is available from DeepInfra, Hyperbolic, Fireworks, Together.
LongCat-Flash-Chat
QwQ-32B-Preview
Outputs Comparison
Judge for yourself.
Run your own prompts against LongCat-Flash-Chat and QwQ-32B-Preview side-by-side, then vote on the output you prefer.
FAQ
Common questions about LongCat-Flash-Chat vs QwQ-32B-Preview.