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Gemini 4 Argon vs MAI-Thinking-1

Gemini 4 Argon leads the LLM Stats Score 55.1 to 32.9.

Google · Microsoft · Updated for 2026

Which is better?

Gemini 4 Argon leads the overall LLM Stats Score 55.1 to 32.9, 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 MAI-Thinking-1

  • you are already invested in the Microsoft ecosystem

At a glance

The differences that matter most.

Gemini 4 Argon
Google
MAI-Thinking-1
Microsoft
Core performance indexes
LLM Stats Score
55.1
#4
32.9
#116
Reasoning
52.4
#7
33.7
#105
Coding
44.1
#4
19.0
#120
Agents
40.5
#4
12.5
#113
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
— / M
Output price
— / M
— / M
Context window
—
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
Gemini 4 Argon
MAI-Thinking-1
Tool use
30.6#6
10.7#129
Long context
30.6#3
20.3#31
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

19 reported for Gemini 4 Argon · 23 for MAI-Thinking-1

No common benchmarks found

Gemini 4 Argon and MAI-Thinking-1don'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

Input capabilities

Documented input modalities across available providers

Gemini 4 Argon supports multimodal inputs, whereas MAI-Thinking-1 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

MAI-Thinking-1

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under proprietary licenses.

Both models have usage restrictions defined by their respective organizations.

Gemini 4 Argon

Proprietary

Closed source

MAI-Thinking-1

Proprietary

Closed source

Release Timeline

When each model was launched

Gemini 4 Argon was released on 2026-09-30, while MAI-Thinking-1 was released on 2026-06-02.

Gemini 4 Argon is 4 months newer than MAI-Thinking-1.

Gemini 4 Argon

Sep 30, 2026

1 weeks ago

4mo newer
MAI-Thinking-1

Jun 2, 2026

4 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?

Judge for yourself.

Run your own prompts against Gemini 4 Argon and MAI-Thinking-1 side-by-side, then vote on the output you prefer.

Gemini 4 Argon
✓ Preferred
MAI-Thinking-1
Open in Playground

FAQ

Common questions about Gemini 4 Argon vs MAI-Thinking-1.

Which is better, Gemini 4 Argon or MAI-Thinking-1?

Gemini 4 Argon leads the LLM Stats Score 55.1 to 32.9. Gemini 4 Argon is made by Google and MAI-Thinking-1 is made by Microsoft. 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 MAI-Thinking-1 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%. MAI-Thinking-1 scores LongFact: 98.0%, AIME 2025: 97.0%, AIME 2026: 94.5%, GraphWalks: 90.0%, AIR-Bench: 88.0%.

What are the main differences between Gemini 4 Argon and MAI-Thinking-1?

Key differences include LLM Stats Score (55.1 vs 32.9), multimodal support (yes vs no). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 4 Argon and MAI-Thinking-1?

Gemini 4 Argon is developed by Google and MAI-Thinking-1 is developed by Microsoft.

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