LongCat-Flash-Lite vs Particle-1
Particle-1 leads the LLM Stats Score 31.9 to 18.0. LongCat-Flash-Lite is 2.5x cheaper per token.
Meituan · Particle AI · Updated for 2026
Which is better?
Particle-1 leads the overall LLM Stats Score 31.9 to 18.0, ranking #133 overall.
In the 2 individual benchmarks reported for both models, Particle-1 wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, LongCat-Flash-Lite is roughly 2.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Particle-1 also accepts a larger context window (1,048,576 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
- cost matters — it's about 2.5x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Particle-1
- overall performance matters — it scores 31.9 and ranks #133 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 1,048,576 token context window
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Individual benchmarks
13 reported for LongCat-Flash-Lite · 3 for Particle-1
LongCat-Flash-Lite outperforms in 0 benchmarks, while Particle-1 is better at 2 benchmarks (GPQA, MMLU).
Particle-1 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 2.5x cheaper than Particle-1 ($0.25/1M tokens).
For output processing, LongCat-Flash-Lite ($0.40/1M tokens) is 2.5x cheaper than Particle-1 ($1.00/1M tokens).
In conclusion, Particle-1 is more expensive than LongCat-Flash-Lite.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Particle-1 accepts 1,048,576 input tokens compared to LongCat-Flash-Lite's 256,000 tokens. Particle-1 can generate longer responses up to 131,072 tokens, while LongCat-Flash-Lite is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Particle-1 supports multimodal inputs, whereas LongCat-Flash-Lite does not.
Particle-1 can handle both text and other forms of data like images, making it suitable for multimodal applications.
LongCat-Flash-Lite
Particle-1
License
Usage and distribution terms
LongCat-Flash-Lite is licensed under MIT, while Particle-1 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-Lite was released on 2026-02-05, while Particle-1 was released on 2026-10-28.
Particle-1 is 9 months newer than LongCat-Flash-Lite.
Feb 5, 2026
8 months ago
Oct 28, 2026
-3 days ago
8mo 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-Lite is available from Meituan. Particle-1 is available from Particle AI.
LongCat-Flash-Lite
Particle-1
Outputs Comparison
Judge for yourself.
Run your own prompts against LongCat-Flash-Lite and Particle-1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about LongCat-Flash-Lite vs Particle-1.