Gemini 3.6 Flash vs GPT-5.6 Luna
Google vs OpenAI · Prices checked 12 August 2026
There is a 6.6× price gap here. GPT-5.6 Luna blends to $0.500 per million tokens; Gemini 3.6 Flash to $3.30. A single 100K-input, 10K-output job costs $0.032 on GPT-5.6 Luna against $0.225 on Gemini 3.6 Flash.
Neither has a context advantage; both cap at 1,050,000 tokens. Gemini 3.6 Flash was released Jul 2026; GPT-5.6 Luna Jul 2026.
Pricing and capacity
| Metric | Gemini 3.6 Flash | GPT-5.6 Luna | Difference |
|---|---|---|---|
| Input / 1M tokens | $1.50 | $0.200 | 7.5× |
| Output / 1M tokens | $7.50 | $1.20 | 6.3× |
| Blended · 70/30calculated | $3.30 | $0.500 | 6.6× |
| Blended · 50/50calculated | $4.50 | $0.700 | 6.4× |
| Blended · 80/20calculated | $2.70 | $0.400 | 6.8× |
| Blended · 20/80calculated | $6.30 | $1.00 | 6.3× |
| Job cost · 100K + 10Kcalculated | $0.225 | $0.032 | 7.0× |
| Job cost · 1M + 100Kcalculated | $2.25 | $0.320 | 7.0× |
| Context window | 1,050,000 | 1,050,000 | level |
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 3.6 Flash
Google · Balanced
Google's current workhorse model, released July 2026 as the practical successor to 3.5 Flash rather than the long-delayed 3.5 Pro. It improves on coding, knowledge work and multimodal handling while reducing token usage by up to 17%, which makes it cheaper to run than its predecessor on the same task even before the headline rate is compared.
- Up to 17% fewer tokens per task than 3.5 Flash
- Coding and knowledge work
- Multimodal input including audio and video
- 1M-token context
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 3.6 Flash or GPT-5.6 Luna?
There is a 6.6× price gap here. GPT-5.6 Luna blends to $0.500 per million tokens; Gemini 3.6 Flash to $3.30. A single 100K-input, 10K-output job costs $0.032 on GPT-5.6 Luna against $0.225 on Gemini 3.6 Flash. 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 3.6 Flash or GPT-5.6 Luna?
Neither has a context advantage; both cap at 1,050,000 tokens. 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 3.6 Flash 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.