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Gemini 4 Argon vs GLM-5.3-Flash

Gemini 4 Argon leads the LLM Stats Score 55.1 to 48.9.

Google · Zhipu AI · Updated for 2026

Which is better?

Gemini 4 Argon leads the overall LLM Stats Score 55.1 to 48.9, ranking #4 overall.

In the 3 individual benchmarks reported for both models, Gemini 4 Argon wins 3; this is a narrower head-to-head signal than the composite indexes.

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 coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 3 of 3 exact shared results
  • you want the most recent training data — it shipped Sep 2026

Choose GLM-5.3-Flash

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

At a glance

The differences that matter most.

Gemini 4 Argon
Google
GLM-5.3-Flash
Zhipu AI
Core performance indexes
LLM Stats Score
55.1
#4
48.9
#24
Reasoning
52.4
#7
47.8
#23
Coding
44.1
#4
32.5
#45
Agents
40.5
#4
35.1
#22
Cost, coverage & limits
Benchmark wins
3 of 3
0 of 3
Input price
— / M
$0.15 / M
Output price
— / M
$0.50 / M
Context window
—
1,048,576

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
Gemini 4 Argon
GLM-5.3-Flash
Vision
36.8#8
30.9#32
Tool use
30.6#6
28.3#19
Multimodal
36.9#8
30.6#33
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

19 reported for Gemini 4 Argon · 15 for GLM-5.3-Flash

3 shared

Gemini 4 Argon outperforms in 3 benchmarks (Agents' Last Exam, AutomationBench, DeepSWE 1.1), while GLM-5.3-Flash is better at 0 benchmarks.

Gemini 4 Argon significantly outperforms across most benchmarks.

Thu Oct 08 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only GLM-5.3-Flash specifies input context (1,048,576 tokens). Only GLM-5.3-Flash specifies output context (1,048,576 tokens).

Google
Gemini 4 Argon
Input- tokens
Output- tokens
Zhipu AI
GLM-5.3-Flash
Input1,048,576 tokens
Output1,048,576 tokens
Thu Oct 08 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Gemini 4 Argon and GLM-5.3-Flash support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Gemini 4 Argon

Text
Images
Audio
Video

GLM-5.3-Flash

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 4 Argon is licensed under a proprietary license, while GLM-5.3-Flash uses MIT.

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

Gemini 4 Argon

Proprietary

Closed source

GLM-5.3-Flash

MIT

Open weights

Release Timeline

When each model was launched

Gemini 4 Argon was released on 2026-09-30, while GLM-5.3-Flash was released on 2026-08-26.

Gemini 4 Argon is 1 month newer than GLM-5.3-Flash.

Gemini 4 Argon

Sep 30, 2026

1 weeks ago

1mo newer
GLM-5.3-Flash

Aug 26, 2026

1 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 GLM-5.3-Flash side-by-side, then vote on the output you prefer.

Gemini 4 Argon
✓ Preferred
GLM-5.3-Flash
Open in Playground

FAQ

Common questions about Gemini 4 Argon vs GLM-5.3-Flash.

Which is better, Gemini 4 Argon or GLM-5.3-Flash?

Gemini 4 Argon leads the LLM Stats Score 55.1 to 48.9. Gemini 4 Argon is made by Google and GLM-5.3-Flash is made by Zhipu AI. 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 GLM-5.3-Flash 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%. GLM-5.3-Flash scores CharXiv-R: 89.4%, Terminal-Bench 2.1: 84.3%, MMVU: 80.5%, Toolathlon: 78.4%, Chartography: 78.0%.

What are the context window sizes for Gemini 4 Argon and GLM-5.3-Flash?

Gemini 4 Argon supports an unknown number of tokens and GLM-5.3-Flash supports 1.0M 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 GLM-5.3-Flash?

Key differences include LLM Stats Score (55.1 vs 48.9), licensing (Proprietary vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 4 Argon and GLM-5.3-Flash?

Gemini 4 Argon is developed by Google and GLM-5.3-Flash is developed by Zhipu AI.

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