GPT-5.6 Luna vs Gemini 3.5 Flash
OpenAI's GPT-5.6 Luna and Google's Gemini 3.5 Flash both target production language workloads, but they price and behave differently. Here is the side-by-side.
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The short answer
GPT-5.6 Luna is the cheaper option — roughly 7.5x less on a blended workload, and it suits high-volume work on a tight budget. Gemini 3.5 Flash justifies its premium when you need agentic loops and sub-agent fleets.
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 3.5
$1.50 / $9.00
/ 1M tokens (input / output)
Google's most capable Flash model, tuned for the agentic era: sub-agent deployment, multi-step workflows, and rapid coding iterations at scale. Supports search grounding, function calling, structured outputs, and computer use in preview. Note that it is pricier than the Gemini 3 Flash preview it replaced.
Input price
Gemini 3.5 Flash is 7.5x the price than GPT-5.6 Luna on input tokens.
Output price
Gemini 3.5 Flash is 7.5x 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 3.5 Flash | Difference |
|---|---|---|---|
| Light — 1M in / 200K out | $0 | $3 | $3 |
| Moderate — 10M in / 2M out | $4 | $33 | $29 |
| Heavy — 100M in / 20M out | $44 | $330 | $286 |
Specification comparison
| Attribute | GPT-5.6 Luna | Gemini 3.5 Flash |
|---|---|---|
| Input (/ 1M tokens) | $0.20 | $1.50 |
| Output (/ 1M tokens) | $1.20 | $9.00 |
| 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 | 2025-01 |
| Relative latency | low | low |
| Open weights | No | No |
| API model ID | gpt-5.6-luna | gemini-3.5-flash |
| Status | stable | stable |
GPT-5.6 Luna: Cut 80% from the $1/$6 launch price on 2026-07-30.
Gemini 3.5 Flash: Flat rate at any context length, unlike Gemini 3.1 Pro's 200K cliff.
Choose GPT-5.6 Luna if…
- Classification and content moderation
- High-frequency agent subtasks
- Bulk summarization
- Cost-sensitive chat features
Choose Gemini 3.5 Flash if…
- Sub-agent fleets and orchestration
- Fast coding iteration loops
- Search-grounded answers
- Multimodal ingestion at scale
Frequently asked
Is GPT-5.6 Luna or Gemini 3.5 Flash cheaper?
GPT-5.6 Luna is cheaper. On a blended 3:1 input-to-output workload it costs about 7.5x less than Gemini 3.5 Flash.
Which has the larger context window, GPT-5.6 Luna or Gemini 3.5 Flash?
Both accept up to 1.05M tokens, so context is not a differentiator here.
Should I use GPT-5.6 Luna or Gemini 3.5 Flash?
Pick GPT-5.6 Luna for high-volume work on a tight budget. Pick Gemini 3.5 Flash for agentic loops and sub-agent fleets. If cost dominates the decision, GPT-5.6 Luna wins; if you need the capability ceiling, benchmark both on your own evals before committing.