Model Comparison

Gemini 3.5 Flash Cyber vs LongCat-Flash-ThinkingWhich is better in 2026?

Comparing Gemini 3.5 Flash Cyber and LongCat-Flash-Thinking across benchmarks, pricing, and capabilities.

Verdict: Gemini 3.5 Flash Cyber vs LongCat-Flash-Thinking — which is better?

Gemini 3.5 Flash Cyber (by Google) and LongCat-Flash-Thinking (by Meituan) 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.

Choose Gemini 3.5 Flash Cyber if…

  • you want the most recent training data — it shipped Jul 2026

Choose LongCat-Flash-Thinking if…

  • you need open weights you can self-host or fine-tune

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Gemini 3.5 Flash Cyber and LongCat-Flash-Thinkingdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Context Window

Maximum input and output token capacity

Only LongCat-Flash-Thinking specifies input context (128,000 tokens). Only LongCat-Flash-Thinking specifies output context (128,000 tokens).

Google
Gemini 3.5 Flash Cyber
Input- tokens
Output- tokens
Meituan
LongCat-Flash-Thinking
Input128,000 tokens
Output128,000 tokens
Tue Jul 21 2026 • llm-stats.com

License

Usage and distribution terms

Gemini 3.5 Flash Cyber is licensed under a proprietary license, while LongCat-Flash-Thinking uses MIT.

License differences may affect how you can use these models in commercial or open-source projects.

Gemini 3.5 Flash Cyber

Proprietary

Closed source

LongCat-Flash-Thinking

MIT

Open weights

Release Timeline

When each model was launched

Gemini 3.5 Flash Cyber was released on 2026-07-21, while LongCat-Flash-Thinking was released on 2025-09-22.

Gemini 3.5 Flash Cyber is 10 months newer than LongCat-Flash-Thinking.

Gemini 3.5 Flash Cyber

Jul 21, 2026

0 days ago

10mo newer
LongCat-Flash-Thinking

Sep 22, 2025

10 months ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Google

No standout differentiators in the data we have for this pair.

Meituan
Larger context window (128,000 tokens)
Has open weights

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against Gemini 3.5 Flash Cyber and LongCat-Flash-Thinking side-by-side, then vote on the output you prefer.

Gemini 3.5 Flash Cyber
✓ Preferred
LongCat-Flash-Thinking
Open in Playground
AI Model Comparison Table
Feature
Google
Gemini 3.5 Flash Cyber
Meituan
LongCat-Flash-Thinking

FAQ

Common questions about Gemini 3.5 Flash Cyber vs LongCat-Flash-Thinking.

Which is better, Gemini 3.5 Flash Cyber or LongCat-Flash-Thinking?

Gemini 3.5 Flash Cyber (Google) and LongCat-Flash-Thinking (Meituan) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does Gemini 3.5 Flash Cyber compare to LongCat-Flash-Thinking in benchmarks?

Gemini 3.5 Flash Cyber scores CyberGym: 83.2%. LongCat-Flash-Thinking scores MATH-500: 99.2%, ZebraLogic: 95.5%, AIME 2024: 93.3%, AIME 2025: 90.6%, MMLU-Redux: 89.3%.

What are the context window sizes for Gemini 3.5 Flash Cyber and LongCat-Flash-Thinking?

Gemini 3.5 Flash Cyber supports an unknown number of tokens and LongCat-Flash-Thinking supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemini 3.5 Flash Cyber and LongCat-Flash-Thinking?

Key differences include licensing (Proprietary vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 3.5 Flash Cyber and LongCat-Flash-Thinking?

Gemini 3.5 Flash Cyber is developed by Google and LongCat-Flash-Thinking is developed by Meituan.

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