Gemini 3.1 Pro vs GPT-5.6 Luna
Google vs OpenAI · Prices checked 12 August 2026
There is a 10.0× price gap here. GPT-5.6 Luna blends to $0.500 per million tokens; Gemini 3.1 Pro to $5.00. A single 100K-input, 10K-output job costs $0.032 on GPT-5.6 Luna against $0.320 on Gemini 3.1 Pro.
GPT-5.6 Luna reads more in one request: 1,050,000 tokens of context against 1,000,000.
Pricing and capacity
| Metric | Gemini 3.1 Pro | GPT-5.6 Luna | Difference |
|---|---|---|---|
| Input / 1M tokens | $2.00 | $0.200 | 10.0× |
| Output / 1M tokens | $12.00 | $1.20 | 10.0× |
| Blended · 70/30calculated | $5.00 | $0.500 | 10.0× |
| Blended · 50/50calculated | $7.00 | $0.700 | 10.0× |
| Blended · 80/20calculated | $4.00 | $0.400 | 10.0× |
| Blended · 20/80calculated | $10.00 | $1.00 | 10.0× |
| Job cost · 100K + 10Kcalculated | $0.320 | $0.032 | 10.0× |
| Job cost · 1M + 100Kcalculated | $3.20 | $0.320 | 10.0× |
| Context window | 1,000,000 | 1,050,000 | 5% |
Input and output rates are as published by each provider. Blended and job-cost rows are calculated comparison metrics, not published prices — how they are derived.
Benchmarks
These two models do not currently report scores on any of the same benchmark suites, so there is no like-for-like capability comparison to show. Rather than pad the page with one-sided numbers, the benchmark leaderboards list every score we do hold.
What each model is for
Gemini 3.1 Pro
Google · Frontier
A mid-cycle upgrade to Gemini 3 Pro, released after rapid iteration on feedback from the November 3 Pro launch. Google positions it for the most complex tasks, with the clearest gains in ambitious agentic workflows. Keeps the 1M-token context window and full multimodal input.
- Agentic workflow execution
- Complex multi-step reasoning
- 1M-token context
- Text, image, audio and video input
GPT-5.6 Luna
OpenAI · Efficient
The fastest and most affordable GPT-5.6 tier, a deliberately low-reasoning lane for high-volume work where speed and cost are the binding constraints rather than depth. It keeps the family's 1M-token context window at $0.20/$1.20 per MTok, which is 25× cheaper than Sol on input, with cached input at $0.02.
- Lowest cost in the GPT-5.6 family, 25× cheaper input than Sol
- Fast responses
- High-volume throughput
- 1M-token context
Frequently asked questions
Which is cheaper, Gemini 3.1 Pro or GPT-5.6 Luna?
There is a 10.0× price gap here. GPT-5.6 Luna blends to $0.500 per million tokens; Gemini 3.1 Pro to $5.00. A single 100K-input, 10K-output job costs $0.032 on GPT-5.6 Luna against $0.320 on Gemini 3.1 Pro. Blended cost weights input at 70% and output at 30%; price your own token split for an exact answer, since the cheaper model on a blended basis is not always cheaper for your workload.
Which has the larger context window, Gemini 3.1 Pro or GPT-5.6 Luna?
GPT-5.6 Luna reads more in one request: 1,050,000 tokens of context against 1,000,000. The context window caps everything in a single request: prompt, retrieved documents, conversation history and the model’s own output all share it.
Can I compare Gemini 3.1 Pro and GPT-5.6 Luna on my own numbers?
Yes. Open both in the side-by-side comparison tool to see every field at once, or use the token calculator to price your actual prompt and monthly request volume against each model. Both are free and need no sign-up.
Price it for your own workload
Related matchups
Terms used on this page
Prices and scores are recomputed on every deploy from the catalogue. Prices checked 12 August 2026.