Gemini Diffusion vs LongCat-Flash-Thinking Comparison

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

Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

Gemini Diffusion outperforms in 0 benchmarks, while LongCat-Flash-Thinking is better at 4 benchmarks (AIME 2025, GPQA, LiveCodeBench, SWE-Bench Verified).

LongCat-Flash-Thinking significantly outperforms across most benchmarks.

Mon Mar 16 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Mon Mar 16 2026 • llm-stats.com
Google
Gemini Diffusion
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Meituan
LongCat-Flash-Thinking
Input tokens$0.30
Output tokens$1.20
Best providerMeituan
Notice missing or incorrect data?Start an Issue

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 Diffusion
Input- tokens
Output- tokens
Meituan
LongCat-Flash-Thinking
Input128,000 tokens
Output128,000 tokens
Mon Mar 16 2026 • llm-stats.com

License

Usage and distribution terms

Gemini Diffusion 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 Diffusion

Proprietary

Closed source

LongCat-Flash-Thinking

MIT

Open weights

Release Timeline

When each model was launched

Gemini Diffusion was released on 2025-05-20, while LongCat-Flash-Thinking was released on 2025-09-22.

LongCat-Flash-Thinking is 4 months newer than Gemini Diffusion.

Gemini Diffusion

May 20, 2025

10 months ago

LongCat-Flash-Thinking

Sep 22, 2025

5 months ago

4mo newer

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

Larger context window (128,000 tokens)
Has open weights
Higher AIME 2025 score (90.6% vs 23.3%)
Higher GPQA score (81.5% vs 40.4%)
Higher LiveCodeBench score (79.4% vs 30.9%)
Higher SWE-Bench Verified score (59.4% vs 22.9%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini Diffusion
Meituan
LongCat-Flash-Thinking