GPT-5.6 Luna vs Gemini 3.1 Pro
OpenAI's GPT-5.6 Luna and Google's Gemini 3.1 Pro both target production language workloads, but they price and behave differently. Here is the side-by-side.
Pricing checked against provider documentation on . How we verify
The short answer
GPT-5.6 Luna is the cheaper option — roughly 10.0x less on a blended workload, and it suits high-volume work on a tight budget. Gemini 3.1 Pro justifies its premium when you need best price-to-reasoning ratio.
OpenAI • GPT-5.6
$0.20 / $1.20
/ 1M tokens (input / output)
After an 80% price cut in July 2026, Luna became the value outlier among frontier-family models: it outperforms the previous generation's top-end Opus tier on coding evals while costing about a fiftieth of Fable 5 per input token. This is the model to route bulk traffic through in a tiered architecture.
Google • Gemini 3.1
$2.00 / $12.00
/ 1M tokens (input / output)
Google's shipping flagship while 3.5 Pro remains unreleased, and the cheapest frontier model by a wide margin. It still tops several hard-reasoning boards including GPQA Diamond and ARC-AGI-2, making it the value choice for research-style workloads — provided you keep prompts under 200K tokens, where the price doubles.
Input price
Gemini 3.1 Pro is 10.0x the price than GPT-5.6 Luna on input tokens.
Output price
Gemini 3.1 Pro is 10.0x the price than GPT-5.6 Luna on output tokens — usually the side that dominates the bill.
Monthly cost at three workload sizes
Standard (non-batch, non-cached) rates. Reasoning models will exceed these figures because thinking tokens bill as output.
| Workload | GPT-5.6 Luna | Gemini 3.1 Pro | Difference |
|---|---|---|---|
| Light — 1M in / 200K out | $0 | $4 | $4 |
| Moderate — 10M in / 2M out | $4 | $44 | $40 |
| Heavy — 100M in / 20M out | $44 | $440 | $396 |
Specification comparison
| Attribute | GPT-5.6 Luna | Gemini 3.1 Pro |
|---|---|---|
| Input (/ 1M tokens) | $0.20 | $2.00 |
| Output (/ 1M tokens) | $1.20 | $12.00 |
| Cached input | $0.02 | — |
| Context window | 1,048,576 tokens | 1,048,576 tokens |
| Max output | 128,000 tokens | 65,536 tokens |
| Native reasoning | Yes | Yes |
| Knowledge cutoff | 2026-02 | 2025-06 |
| Relative latency | low | medium |
| Open weights | No | No |
| API model ID | gpt-5.6-luna | gemini-3.1-pro-preview |
| Status | stable | preview |
GPT-5.6 Luna: Cut 80% from the $1/$6 launch price on 2026-07-30.
Gemini 3.1 Pro: Prompts over 200K tokens reprice to $4 input / $18 output per 1M.
Choose GPT-5.6 Luna if…
- Classification and content moderation
- High-frequency agent subtasks
- Bulk summarization
- Cost-sensitive chat features
Choose Gemini 3.1 Pro if…
- Hard reasoning and research tasks
- Long-context document and video analysis
- Native multimodal pipelines
- Cost-conscious frontier workloads
Frequently asked
Is GPT-5.6 Luna or Gemini 3.1 Pro cheaper?
GPT-5.6 Luna is cheaper. On a blended 3:1 input-to-output workload it costs about 10.0x less than Gemini 3.1 Pro.
Which has the larger context window, GPT-5.6 Luna or Gemini 3.1 Pro?
Both accept up to 1.05M tokens, so context is not a differentiator here.
Should I use GPT-5.6 Luna or Gemini 3.1 Pro?
Pick GPT-5.6 Luna for high-volume work on a tight budget. Pick Gemini 3.1 Pro for best price-to-reasoning ratio. If cost dominates the decision, GPT-5.6 Luna wins; if you need the capability ceiling, benchmark both on your own evals before committing.