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Gemini 4 Argon vs LongCat-Flash-Thinking

Gemini 4 Argon leads the LLM Stats Score 55.1 to 28.7.

Google · Meituan · Updated for 2026

Which is better?

Gemini 4 Argon leads the overall LLM Stats Score 55.1 to 28.7, ranking #4 overall.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Gemini 4 Argon

  • overall performance matters — it scores 55.1 and ranks #4 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you want the most recent training data — it shipped Sep 2026

Choose LongCat-Flash-Thinking

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

At a glance

The differences that matter most.

Gemini 4 Argon
Google
LongCat-Flash-Thinking
Meituan
Core performance indexes
LLM Stats Score
55.1
#4
28.7
#148
Reasoning
52.4
#7
28.9
#141
Coding
44.1
#4
13.9
#149
Agents
40.5
#4
12.9
#110
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$0.30 / M
Output price
— / M
$1.20 / M
Context window
—
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Gemini 4 Argon
LongCat-Flash-Thinking
Tool use
30.6#6
15.7#95
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

19 reported for Gemini 4 Argon · 14 for LongCat-Flash-Thinking

No common benchmarks found

Gemini 4 Argon and LongCat-Flash-Thinkingdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

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 4 Argon
Input- tokens
Output- tokens
Meituan
LongCat-Flash-Thinking
Input128,000 tokens
Output128,000 tokens
Fri Oct 09 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Gemini 4 Argon supports multimodal inputs, whereas LongCat-Flash-Thinking does not.

Gemini 4 Argon can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemini 4 Argon

Text
Images
Audio
Video

LongCat-Flash-Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 4 Argon 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 4 Argon

Proprietary

Closed source

LongCat-Flash-Thinking

MIT

Open weights

Release Timeline

When each model was launched

Gemini 4 Argon was released on 2026-09-30, while LongCat-Flash-Thinking was released on 2025-09-22.

Gemini 4 Argon is 12 months newer than LongCat-Flash-Thinking.

Gemini 4 Argon

Sep 30, 2026

1 weeks ago

1.0yr newer
LongCat-Flash-Thinking

Sep 22, 2025

1.0 years 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?

Judge for yourself.

Run your own prompts against Gemini 4 Argon and LongCat-Flash-Thinking side-by-side, then vote on the output you prefer.

Gemini 4 Argon
✓ Preferred
LongCat-Flash-Thinking
Open in Playground

FAQ

Common questions about Gemini 4 Argon vs LongCat-Flash-Thinking.

Which is better, Gemini 4 Argon or LongCat-Flash-Thinking?

Gemini 4 Argon leads the LLM Stats Score 55.1 to 28.7. Gemini 4 Argon 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 4 Argon compare to LongCat-Flash-Thinking in benchmarks?

Gemini 4 Argon scores Graphwalks BFS <128k: 99.7%, Vibe Code Bench: 91.9%, LVBench: 91.7%, LABBench2: 88.8%, Graphwalks BFS >128k: 84.2%. 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 4 Argon and LongCat-Flash-Thinking?

Gemini 4 Argon 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 4 Argon and LongCat-Flash-Thinking?

Key differences include LLM Stats Score (55.1 vs 28.7), multimodal support (yes vs no), licensing (Proprietary vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 4 Argon and LongCat-Flash-Thinking?

Gemini 4 Argon is developed by Google and LongCat-Flash-Thinking is developed by Meituan.

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