Gemini 2.5 Pro vs GPT-5.6 Luna
Google vs OpenAI · Prices checked 12 August 2026
On blended cost GPT-5.6 Luna undercuts Gemini 2.5 Pro by about 7.8×: $0.500 per million tokens versus $3.88. A single 100K-input, 10K-output job costs $0.032 on GPT-5.6 Luna against $0.225 on Gemini 2.5 Pro.
Of the 2 shared benchmarks, GPT-5.6 Luna takes 2. The widest gap is on LMArena Elo, where GPT-5.6 Luna leads by 62 points. On context, GPT-5.6 Luna is the larger at 1,050,000 tokens versus 1,000,000. Gemini 2.5 Pro was released 2025; GPT-5.6 Luna Jul 2026.
Pricing and capacity
| Metric | Gemini 2.5 Pro | GPT-5.6 Luna | Difference |
|---|---|---|---|
| Input / 1M tokens | $1.25 | $0.200 | 6.3× |
| Output / 1M tokens | $10.00 | $1.20 | 8.3× |
| Blended · 70/30calculated | $3.88 | $0.500 | 7.8× |
| Blended · 50/50calculated | $5.63 | $0.700 | 8.0× |
| Blended · 80/20calculated | $3.00 | $0.400 | 7.5× |
| Blended · 20/80calculated | $8.25 | $1.00 | 8.3× |
| Job cost · 100K + 10Kcalculated | $0.225 | $0.032 | 7.0× |
| Job cost · 1M + 100Kcalculated | $2.25 | $0.320 | 7.0× |
| 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
| Benchmark | Gemini 2.5 Pro | GPT-5.6 Luna | Leader |
|---|---|---|---|
| GPQA Diamond | 84% | 92.3% | GPT-5.6 Luna |
| LMArena Elo | 1389 Elo | 1451 Elo | GPT-5.6 Luna |
Only suites both models report are listed, so a missing score is never shown as a loss. Figures are provider-published or from public leaderboards and are not independently re-run.
What each model is for
Gemini 2.5 Pro
Google · Frontier
Google's flagship Gemini. 1M-token context, native multimodal across text, image, audio and video, with thinking enabled.
- 1M context (2M in private beta)
- Native video + audio understanding
- Strong reasoning with thinking
- Tight Google ecosystem
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 2.5 Pro or GPT-5.6 Luna?
On blended cost GPT-5.6 Luna undercuts Gemini 2.5 Pro by about 7.8×: $0.500 per million tokens versus $3.88. A single 100K-input, 10K-output job costs $0.032 on GPT-5.6 Luna against $0.225 on Gemini 2.5 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 performs better, Gemini 2.5 Pro or GPT-5.6 Luna?
Of the 2 shared benchmarks, GPT-5.6 Luna takes 2. The widest gap is on LMArena Elo, where GPT-5.6 Luna leads by 62 points. These are the figures each provider or public leaderboard publishes, not results we re-run, and a benchmark average can hide the specific behaviour your workload depends on.
Which has the larger context window, Gemini 2.5 Pro or GPT-5.6 Luna?
On context, GPT-5.6 Luna is the larger at 1,050,000 tokens versus 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 2.5 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.