LongCat-Flash-Lite vs Qwen2.5-Coder 32B Instruct
LongCat-Flash-Lite leads the LLM Stats Score 18.7 to 2.0. Qwen2.5-Coder 32B Instruct is 1.9x cheaper per token.
Meituan · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
LongCat-Flash-Lite leads the overall LLM Stats Score 18.7 to 2.0, ranking #209 overall.
In the 2 individual benchmarks reported for both models, LongCat-Flash-Lite wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, Qwen2.5-Coder 32B Instruct is roughly 1.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
LongCat-Flash-Lite also accepts a larger context window (256,000 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-Lite
- overall performance matters — it scores 18.7 and ranks #209 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 256,000 token context window
- you want the most recent training data — it shipped Feb 2026
Choose Qwen2.5-Coder 32B Instruct
- cost matters — it's about 1.9x cheaper per token
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
13 reported for LongCat-Flash-Lite · 15 for Qwen2.5-Coder 32B Instruct
LongCat-Flash-Lite outperforms in 2 benchmarks (MMLU, MMLU-Pro), while Qwen2.5-Coder 32B Instruct is better at 0 benchmarks.
LongCat-Flash-Lite 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-Lite ($0.10/1M tokens) is 1.1x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).
For output processing, LongCat-Flash-Lite ($0.40/1M tokens) is 4.4x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).
In conclusion, LongCat-Flash-Lite is more expensive than Qwen2.5-Coder 32B Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
LongCat-Flash-Lite has 36.5B more parameters than Qwen2.5-Coder 32B Instruct, making it 114.1% larger.
Context Window
Maximum input and output token capacity
LongCat-Flash-Lite accepts 256,000 input tokens compared to Qwen2.5-Coder 32B Instruct's 128,000 tokens. Both models can generate responses up to 128,000 tokens.
License
Usage and distribution terms
LongCat-Flash-Lite is licensed under MIT, while Qwen2.5-Coder 32B Instruct 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-Lite was released on 2026-02-05, while Qwen2.5-Coder 32B Instruct was released on 2024-09-19.
LongCat-Flash-Lite is 17 months newer than Qwen2.5-Coder 32B Instruct.
Feb 5, 2026
7 months ago
1.4yr newerSep 19, 2024
2.0 years ago
Knowledge 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-Lite is available from Meituan. Qwen2.5-Coder 32B Instruct is available from Lambda, DeepInfra, Hyperbolic, Fireworks.
LongCat-Flash-Lite
Qwen2.5-Coder 32B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against LongCat-Flash-Lite and Qwen2.5-Coder 32B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about LongCat-Flash-Lite vs Qwen2.5-Coder 32B Instruct.