Model Comparison
LongCat-Flash-Thinking vs o4-miniWhich is better in 2026?
o4-mini shows notably better performance in the majority of benchmarks. LongCat-Flash-Thinking is 3.7x cheaper per token.
Verdict: LongCat-Flash-Thinking vs o4-mini — which is better?
LongCat-Flash-Thinking (by Meituan) and o4-mini (by OpenAI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
LongCat-Flash-Thinking outperforms in 1 benchmarks (GPQA), while o4-mini is better at 3 benchmarks (AIME 2024, AIME 2025, SWE-Bench Verified). o4-mini shows notably better performance in the majority of benchmarks.
On price, LongCat-Flash-Thinking is roughly 3.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
o4-mini also accepts a larger context window (200,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose LongCat-Flash-Thinking if…
- cost matters — it's about 3.7x cheaper per token
- you want the most recent training data — it shipped Sep 2025
- you need open weights you can self-host or fine-tune
Choose o4-mini if…
- you want the strongest raw capability — it leads on 3 of 4 shared benchmarks
- you process long inputs — it offers a 200,000 token context window
Performance Benchmarks
Comparative analysis across standard metrics
LongCat-Flash-Thinking outperforms in 1 benchmarks (GPQA), while o4-mini is better at 3 benchmarks (AIME 2024, AIME 2025, SWE-Bench Verified).
o4-mini shows notably better performance in the majority of benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, LongCat-Flash-Thinking ($0.30/1M tokens) is 3.7x cheaper than o4-mini ($1.10/1M tokens).
For output processing, LongCat-Flash-Thinking ($1.20/1M tokens) is 3.7x cheaper than o4-mini ($4.40/1M tokens).
In conclusion, o4-mini is more expensive than LongCat-Flash-Thinking.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
o4-mini accepts 200,000 input tokens compared to LongCat-Flash-Thinking's 128,000 tokens. LongCat-Flash-Thinking can generate longer responses up to 128,000 tokens, while o4-mini is limited to 100,000 tokens.
Input Capabilities
Supported data types and modalities
o4-mini supports multimodal inputs, whereas LongCat-Flash-Thinking does not.
o4-mini can handle both text and other forms of data like images, making it suitable for multimodal applications.
LongCat-Flash-Thinking
o4-mini
License
Usage and distribution terms
LongCat-Flash-Thinking is licensed under MIT, while o4-mini 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-Thinking was released on 2025-09-22, while o4-mini was released on 2025-04-16.
LongCat-Flash-Thinking is 5 months newer than o4-mini.
Sep 22, 2025
10 months ago
5mo newerApr 16, 2025
1.3 years ago
Knowledge Cutoff
When training data ends
o4-mini has a documented knowledge cutoff of 2024-05-31, while LongCat-Flash-Thinking's cutoff date is not specified.
We can confirm o4-mini's training data extends to 2024-05-31, but cannot make a direct comparison without LongCat-Flash-Thinking's cutoff date.
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May 2024
Provider Availability
LongCat-Flash-Thinking is available from Meituan. o4-mini is available from OpenAI.
LongCat-Flash-Thinking
o4-mini
Outputs Comparison
Key Takeaways
o4-mini
View detailsOpenAI
LongCat-Flash-Thinkingo4-miniDetailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against LongCat-Flash-Thinking and o4-mini side-by-side, then vote on the output you prefer.
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FAQ
Common questions about LongCat-Flash-Thinking vs o4-mini.