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Gemini 4 Argon vs GPT-4

Gemini 4 Argon leads the LLM Stats Score 55.1 to 3.0.

Google · OpenAI · Updated for 2026

Which is better?

Gemini 4 Argon leads the overall LLM Stats Score 55.1 to 3.0, 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 GPT-4

  • you want predictable pricing at $30.00/M input and $60.00/M output

At a glance

The differences that matter most.

Core performance indexes
55.1
#4
3.0
#326
52.4
#7
3.0
#318
44.1
#4
-5.2
#275
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$30.00 / M
Output price
— / M
$60.00 / M
Context window
—
32,768

Individual benchmarks

19 reported for Gemini 4 Argon · 12 for GPT-4

No common benchmarks found

Gemini 4 Argon and GPT-4don'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 GPT-4 specifies input context (32,768 tokens). Only GPT-4 specifies output context (32,768 tokens).

Google
Gemini 4 Argon
Input- tokens
Output- tokens
OpenAI
GPT-4
Input32,768 tokens
Output32,768 tokens
Thu Oct 08 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Gemini 4 Argon and GPT-4 support multimodal inputs.

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

Gemini 4 Argon

Text
Images
Audio
Video

GPT-4

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

GPT-4

Proprietary

Closed source

Release Timeline

When each model was launched

Gemini 4 Argon was released on 2026-09-30, while GPT-4 was released on 2023-06-13.

Gemini 4 Argon is 40 months newer than GPT-4.

Gemini 4 Argon

Sep 30, 2026

1 weeks ago

3.3yr newer
GPT-4

Jun 13, 2023

3.3 years ago

Knowledge Cutoff

When training data ends

GPT-4 has a documented knowledge cutoff of 2022-12-31, while Gemini 4 Argon's cutoff date is not specified.

We can confirm GPT-4's training data extends to 2022-12-31, but cannot make a direct comparison without Gemini 4 Argon's cutoff date.

Gemini 4 Argon

—

GPT-4

Dec 2022

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

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

Gemini 4 Argon
✓ Preferred
GPT-4
Open in Playground

FAQ

Common questions about Gemini 4 Argon vs GPT-4.

Which is better, Gemini 4 Argon or GPT-4?

Gemini 4 Argon leads the LLM Stats Score 55.1 to 3.0. Gemini 4 Argon is made by Google and GPT-4 is made by OpenAI. 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 GPT-4 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%. GPT-4 scores AI2 Reasoning Challenge (ARC): 96.3%, HellaSwag: 95.3%, Uniform Bar Exam: 90.0%, SAT Math: 89.0%, LSAT: 88.0%.

What are the context window sizes for Gemini 4 Argon and GPT-4?

Gemini 4 Argon supports an unknown number of tokens and GPT-4 supports 33K 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 GPT-4?

Key differences include LLM Stats Score (55.1 vs 3.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 4 Argon and GPT-4?

Gemini 4 Argon is developed by Google and GPT-4 is developed by OpenAI.