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Gemini 2.5 Flash vs LongCat-Flash-Thinking

LongCat-Flash-Thinking leads the LLM Stats Score 28.8 to 21.9. LongCat-Flash-Thinking is 1.6x cheaper per token.

Google · Meituan · Updated for 2026

Which is better?

LongCat-Flash-Thinking leads the overall LLM Stats Score 28.8 to 21.9, ranking #124 overall.

The models split the 4 individual benchmarks reported for both models evenly.

On price, LongCat-Flash-Thinking is roughly 1.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Gemini 2.5 Flash 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 Gemini 2.5 Flash

  • you process long inputs — it offers a 1,048,576 token context window

Choose LongCat-Flash-Thinking

  • overall performance matters — it scores 28.8 and ranks #124 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • cost matters — it's about 1.6x 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

At a glance

The differences that matter most.

Gemini 2.5 Flash
Google
LongCat-Flash-Thinking
Meituan
Core performance indexes
LLM Stats Score
21.9
#172
28.8
#124
Reasoning
21.6
#170
28.9
#116
Coding
8.7
#172
14.3
#127
Cost, coverage & limits
Benchmark wins
2 of 4
2 of 4
Input price
$0.30 / M
$0.30 / M
Output price
$2.50 / M
$1.20 / M
Context window
1,048,576
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Gemini 2.5 Flash
LongCat-Flash-Thinking
Math
16.2#200
28.3#89
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

14 reported for Gemini 2.5 Flash · 14 for LongCat-Flash-Thinking

4 shared

Gemini 2.5 Flash outperforms in 2 benchmarks (GPQA, SWE-Bench Verified), while LongCat-Flash-Thinking is better at 2 benchmarks (AIME 2024, AIME 2025).

Both models are evenly matched across the benchmarks.

Mon Sep 07 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

LongCat-Flash-Thinking costs less

For input processing, Gemini 2.5 Flash ($0.30/1M tokens) costs the same as LongCat-Flash-Thinking ($0.30/1M tokens).

For output processing, Gemini 2.5 Flash ($2.50/1M tokens) is 2.1x more expensive than LongCat-Flash-Thinking ($1.20/1M tokens).

In conclusion, Gemini 2.5 Flash is more expensive than LongCat-Flash-Thinking.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Mon Sep 07 2026 • llm-stats.com
Google
Gemini 2.5 Flash
Input tokens$0.30
Output tokens$2.50
Best providerGoogle
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

Gemini 2.5 Flash accepts 1,048,576 input tokens compared to LongCat-Flash-Thinking's 128,000 tokens. LongCat-Flash-Thinking can generate longer responses up to 128,000 tokens, while Gemini 2.5 Flash is limited to 65,536 tokens.

Google
Gemini 2.5 Flash
Input1,048,576 tokens
Output65,536 tokens
Meituan
LongCat-Flash-Thinking
Input128,000 tokens
Output128,000 tokens
Mon Sep 07 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Gemini 2.5 Flash supports multimodal inputs, whereas LongCat-Flash-Thinking does not.

Gemini 2.5 Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemini 2.5 Flash

Text
Images
Audio
Video

LongCat-Flash-Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 2.5 Flash 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 2.5 Flash

Proprietary

Closed source

LongCat-Flash-Thinking

MIT

Open weights

Release Timeline

When each model was launched

Gemini 2.5 Flash 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 2.5 Flash.

Gemini 2.5 Flash

May 20, 2025

1.3 years ago

LongCat-Flash-Thinking

Sep 22, 2025

11 months ago

4mo newer

Knowledge Cutoff

When training data ends

Gemini 2.5 Flash has a documented knowledge cutoff of 2025-01-31, while LongCat-Flash-Thinking's cutoff date is not specified.

We can confirm Gemini 2.5 Flash's training data extends to 2025-01-31, but cannot make a direct comparison without LongCat-Flash-Thinking's cutoff date.

Gemini 2.5 Flash

Jan 2025

LongCat-Flash-Thinking

—

Provider Availability

Gemini 2.5 Flash is available from Google. LongCat-Flash-Thinking is available from Meituan.

Gemini 2.5 Flash

google logo
Google
Input Price:Input: $0.30/1MOutput Price:Output: $2.50/1M

LongCat-Flash-Thinking

meituan logo
Meituan
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Gemini 2.5 Flash and LongCat-Flash-Thinking side-by-side, then vote on the output you prefer.

Gemini 2.5 Flash
✓ Preferred
LongCat-Flash-Thinking
Open in Playground

FAQ

Common questions about Gemini 2.5 Flash vs LongCat-Flash-Thinking.

Which is better, Gemini 2.5 Flash or LongCat-Flash-Thinking?

LongCat-Flash-Thinking leads the LLM Stats Score 28.8 to 21.9. Gemini 2.5 Flash is made by Google and LongCat-Flash-Thinking is made by Meituan. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Gemini 2.5 Flash compare to LongCat-Flash-Thinking in benchmarks?

Gemini 2.5 Flash scores Global-MMLU-Lite: 88.4%, AIME 2024: 88.0%, FACTS Grounding: 85.3%, GPQA: 82.8%, MMMU: 79.7%. LongCat-Flash-Thinking scores MATH-500: 99.2%, ZebraLogic: 95.5%, AIME 2024: 93.3%, AIME 2025: 90.6%, MMLU-Redux: 89.3%.

Is Gemini 2.5 Flash cheaper than LongCat-Flash-Thinking?

Both models cost $0.30 per million input tokens.

What are the context window sizes for Gemini 2.5 Flash and LongCat-Flash-Thinking?

Gemini 2.5 Flash supports 1.0M 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 2.5 Flash and LongCat-Flash-Thinking?

Key differences include LLM Stats Score (21.9 vs 28.8), context window (1.0M vs 128K), multimodal support (yes vs no), licensing (Proprietary vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 2.5 Flash and LongCat-Flash-Thinking?

Gemini 2.5 Flash is developed by Google and LongCat-Flash-Thinking is developed by Meituan.

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