Choose Google: Gemini 4 Argon if…
- you need audio input — to take speech or audio directly; OpenAI: GPT-5.6 Luna does not advertise it
- you want the newer model — released 2026-10-13, 3 months after the other
Google: Gemini 4 Argon vs OpenAI: GPT-5.6 Luna
Neither wins outright: Google: Gemini 4 Argon is the pick when you need audio input, OpenAI: GPT-5.6 Luna when cost matters at scale.
Key numbers
| Spec | Google: Gemini 4 Argon | OpenAI: GPT-5.6 Luna |
|---|---|---|
| Provider | OpenAI | |
| Input price (per 1M tokens) | $2.00 | $0.20 |
| Output price (per 1M tokens) | $10.00 | $1.20 |
| Blended price (3:1 input/output) | $4.00 | $0.45 |
| Cheaper than … of all models we track | 15% | 55% |
| Context window | 1.0M tokens (~1,573 pages) | 1.1M tokens (~1,575 pages) |
| Larger context than … of all models | 81% | 92% |
| Max output per response | 66K tokens (~49,200 words) | 128K tokens (~96,000 words) |
| Input types | audio, file, image, text, video | file, image, text |
| Output types | text | text |
| Free variant | No | No |
| Listed since | 2026-10-13 | 2026-07-09 |
What it costs for real workloads
Monthly cost at list price for five common workloads. Token counts per unit are stated so you can scale them to your own traffic. A workload that does not fit a model's context window is marked rather than priced.
| Workload (per month) | Google: Gemini 4 Argon | OpenAI: GPT-5.6 Luna | Difference |
|---|---|---|---|
| Customer-support chatbot 50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens) | $350 | $39.00 | OpenAI: GPT-5.6 Luna saves $311 |
| RAG search over documents 20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens) | $340 | $36.00 | OpenAI: GPT-5.6 Luna saves $304 |
| Coding / tool-using agent 2,000 tasks — each a multi-step task with tool calls and file context (60,000 in / 6,000 out tokens) | $360 | $38.40 | OpenAI: GPT-5.6 Luna saves $322 |
| Batch summarisation 10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens) | $220 | $23.20 | OpenAI: GPT-5.6 Luna saves $197 |
| Long-document analysis 500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens) | $110 | $11.20 | OpenAI: GPT-5.6 Luna saves $98.80 |
Capabilities side by side
| Capability | Google: Gemini 4 Argon | OpenAI: GPT-5.6 Luna | What it lets you do |
|---|---|---|---|
| Tool / function calling | ✓ Yes | ✓ Yes | call your APIs and run agent loops |
| Structured output (JSON schema) | ✓ Yes | ✓ Yes | return JSON that validates against your schema |
| Reasoning / thinking mode | ✓ Yes | ✓ Yes | spend extra tokens thinking before answering hard problems |
| Image input | ✓ Yes | ✓ Yes | read screenshots, charts and scanned pages |
| Audio input | ✓ Yes | — | take speech or audio directly |
| File / PDF input | ✓ Yes | ✓ Yes | accept documents without your own parsing step |
| Image output | — | — | generate images, not just text |
| Built-in web search | ✓ Yes | ✓ Yes | answer from live web results |
| Seed (reproducible sampling) | ✓ Yes | ✓ Yes | repeat a generation for tests and evals |
| Log-probabilities | — | — | read token confidence for classification and scoring |
From each model's published parameters and input/output types. “—” means not advertised, not proven absent.
Price history
- Google: Gemini 4 Argon: price unchanged since we started tracking it on 2026-10-14.
- OpenAI: GPT-5.6 Luna: input price raised 50% ($0.10 → $0.20/1M), output price raised 50% ($0.60 → $1.20/1M) on 2026-08-18.
| Date | Model | Input / 1M | Output / 1M |
|---|---|---|---|
| 2026-08-18 | OpenAI: GPT-5.6 Luna | $0.20 | $1.20 |
Which should you choose?
Choose OpenAI: GPT-5.6 Luna if…
- cost matters at scale — it is 89% cheaper on a typical 3:1 input/output mix ($39.00 vs $350 a month for 50,000 support chats)
- you generate long outputs in one go — up to 128K tokens (about 96,000 words) per response
Frequently asked questions
Is Google: Gemini 4 Argon better than OpenAI: GPT-5.6 Luna?
Neither wins outright: Google: Gemini 4 Argon is the pick when you need audio input, OpenAI: GPT-5.6 Luna when cost matters at scale. In short: Google: Gemini 4 Argon when you need audio input, you want the newer model; OpenAI: GPT-5.6 Luna when cost matters at scale, you generate long outputs in one go.
Which is cheaper, Google: Gemini 4 Argon or OpenAI: GPT-5.6 Luna?
OpenAI: GPT-5.6 Luna is cheaper: $0.45 vs $4.00 per 1M tokens at a typical 3:1 input/output mix, 89% less. For 50,000 support conversations a month that is $39.00 against $350.
How much do Google: Gemini 4 Argon and OpenAI: GPT-5.6 Luna cost per million tokens?
Google: Gemini 4 Argon costs $2.00 per 1M input tokens and $10.00 per 1M output tokens; OpenAI: GPT-5.6 Luna costs $0.20 input and $1.20 output. Output tokens are billed separately, so long answers shift the gap.
Which has the bigger context window, Google: Gemini 4 Argon or OpenAI: GPT-5.6 Luna?
OpenAI: GPT-5.6 Luna: 1.1M tokens, about 1,575 pages, against 1.0M (about 1,573 pages) for Google: Gemini 4 Argon.
Do Google: Gemini 4 Argon and OpenAI: GPT-5.6 Luna support function calling and JSON output?
Tool calling — Google: Gemini 4 Argon: yes, OpenAI: GPT-5.6 Luna: yes. JSON-schema structured output — Google: Gemini 4 Argon: yes, OpenAI: GPT-5.6 Luna: yes.
Can Google: Gemini 4 Argon or OpenAI: GPT-5.6 Luna read images?
Yes, both accept image input.
Is Google: Gemini 4 Argon or OpenAI: GPT-5.6 Luna free to use?
No free variant is listed for either; both are pay-per-token.
What is the maximum output length of Google: Gemini 4 Argon and OpenAI: GPT-5.6 Luna?
Google: Gemini 4 Argon can write up to 66K tokens (about 49,200 words) per response; OpenAI: GPT-5.6 Luna up to 128K (about 96,000 words).
When were Google: Gemini 4 Argon and OpenAI: GPT-5.6 Luna released?
Google: Gemini 4 Argon was listed on 2026-10-13; OpenAI: GPT-5.6 Luna on 2026-07-09.
Has the price of Google: Gemini 4 Argon or OpenAI: GPT-5.6 Luna changed?
Google: Gemini 4 Argon: price unchanged since we started tracking it on 2026-10-14. OpenAI: GPT-5.6 Luna: input price raised 50% ($0.10 → $0.20/1M), output price raised 50% ($0.60 → $1.20/1M) on 2026-08-18.
About the two models
Google: Gemini 4 Argon
Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across...
Full Google: Gemini 4 Argon specs →OpenAI: GPT-5.6 Luna
GPT-5.6 Luna is a fast, cost-efficient model in OpenAI's GPT-5.6 series. It is suited for high-volume, latency-sensitive tasks such as chat, classification, and lightweight agentic workflows, providing capable reasoning for...
Full OpenAI: GPT-5.6 Luna specs →