Balanced tiers compared: $2/$12 against $1.50/$7.50 Flash.
gpt-5.6-terra · openai
gemini-3.6-flash · google
Benchmark
| Workload Scenario | GPT-5.6 Terra | Gemini 3.6 Flash | Price Delta |
|---|---|---|---|
| 1M input tokens (raw text) | $2.00 | $1.50 | +$0.50 |
| 1M output tokens (generation) | $12.00 | $7.50 | +$4.50 |
| 1M tokens · 70% input / 30% output mix | $5.00 | $3.30 | +$1.70 |
| Standard chat turn (4K in / 800 out, 50% cached) | $0.014 | $0.0093 | +$0.0047 |
| Monthly scale (10K requests / day) | $4,200.00 | $2,790.00 | +$1,410.00 |
Negative difference = GPT-5.6 Terra is cheaper. Positive = Gemini 3.6 Flash is cheaper.
Scaling Curve
Total cost of a token volume at 70/30 input/output split (uncached). Log-log scale.
Verdict
Gemini 3.6 Flash is cheaper on both input and output rates, so it costs less at every input/output mix. Price alone still isn't the whole decision: capability, latency and context limits (GPT-5.6 Terra: 1.1M, Gemini 3.6 Flash: 1M) may justify the premium for your task.
FAQ
On input, Gemini 3.6 Flash is cheaper ($1.50/M vs $2.00/M). On output, Gemini 3.6 Flash is cheaper ($7.50/M vs $12.00/M). The same model is cheaper on both sides, so it wins at every mix.
A chat-style request (4,000 input + 800 output tokens, 50% cached) costs $0.014 on GPT-5.6 Terra and $0.0093 on Gemini 3.6 Flash — Gemini 3.6 Flash is 1.5× more expensive for that workload.
GPT-5.6 Terra supports 1,050,000 tokens (128K max output); Gemini 3.6 Flash supports 1,048,576 (65.5K max output). GPT-5.6 Terra fits 1.0× more context, which matters for long documents and agents.