Gemini 4 Argon vs GPT-6 Luna
Gemini 4 Argon leads the LLM Stats Score 55.1 to 43.1. GPT-6 Luna is 20.0x cheaper per token.
Google · OpenAI · Updated for 2026
Which is better?
Gemini 4 Argon leads the overall LLM Stats Score 55.1 to 43.1, ranking #4 overall.
In the 3 individual benchmarks reported for both models, Gemini 4 Argon wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, GPT-6 Luna is roughly 20.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-6 Luna also accepts a larger context window (1,050,000 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 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 value its reported benchmark strengths — it wins 2 of 3 exact shared results
- you want the most recent training data — it shipped Sep 2026
Choose GPT-6 Luna
- cost matters — it's about 20.0x cheaper per token
- you process long inputs — it offers a 1,050,000 token context window
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
19 reported for Gemini 4 Argon · 5 for GPT-6 Luna
Gemini 4 Argon outperforms in 2 benchmarks (DeepSWE 1.1, OSWorld 2.0), while GPT-6 Luna is better at 1 benchmark (Agents' Last Exam).
Gemini 4 Argon shows notably better performance in the majority of benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 4 Argon ($2.00/1M tokens) is 20.0x more expensive than GPT-6 Luna ($0.10/1M tokens).
For output processing, Gemini 4 Argon ($10.00/1M tokens) is 20.0x more expensive than GPT-6 Luna ($0.50/1M tokens).
In conclusion, Gemini 4 Argon is more expensive than GPT-6 Luna.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-6 Luna accepts 1,050,000 input tokens compared to Gemini 4 Argon's 1,048,576 tokens. Gemini 4 Argon can generate longer responses up to 1,048,576 tokens, while GPT-6 Luna is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Both Gemini 4 Argon and GPT-6 Luna support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemini 4 Argon
GPT-6 Luna
License
Usage and distribution terms
Both models are licensed under proprietary licenses.
Both models have usage restrictions defined by their respective organizations.
Proprietary
Closed source
Proprietary
Closed source
Release Timeline
When each model was launched
Gemini 4 Argon was released on 2026-09-30, while GPT-6 Luna was released on 2026-09-22.
Gemini 4 Argon is 0 month newer than GPT-6 Luna.
Sep 30, 2026
3 weeks ago
1w newerSep 22, 2026
1 months ago
Knowledge Cutoff
When training data ends
GPT-6 Luna has a documented knowledge cutoff of 2026-05-18, while Gemini 4 Argon's cutoff date is not specified.
We can confirm GPT-6 Luna's training data extends to 2026-05-18, but cannot make a direct comparison without Gemini 4 Argon's cutoff date.
—
May 2026
Provider Availability
Gemini 4 Argon is available from Google. GPT-6 Luna is available from OpenAI.
Gemini 4 Argon
GPT-6 Luna
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemini 4 Argon and GPT-6 Luna side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemini 4 Argon vs GPT-6 Luna.