ColinBuilds.com · Current official OpenAI API pricing
GPT-5.6 Luna
- Input / 1M
- $1.00
- Output / 1M
- $6.00
- OpenAI-published context window
- 1,050,000 tokens
GPT-5.6 Luna / gpt-5.6-luna; OpenAI standard short-context pricing row lists $1.00 input, $0.10 cached input, $1.25 cache writes, and $6.00 output per 1M tokens · as of July 14, 2026
Compare models
Same per-1M input/output rates as above. Enter your monthly token volumes to compare bills.
GPT-5.6 Luna
- Input: 1M × $1.00 = $1.00
- Output: 1M × $6.00 = $6.00
- Total
- $7.00
GPT-4o
- Input: 1M × $2.50 = $2.50
- Output: 1M × $10.00 = $10.00
- Total
- $12.50
Difference
$5.50
GPT-4o costs $5.50 more than GPT-5.6 Luna.
Popular comparisons
30 total featuring GPT-5.6 Luna.
GPT-5.6 Luna is OpenAI’s cost-sensitive GPT-5.6 API model for high-volume applications that still need the GPT-5.6 family rather than an older or unrelated model line.
What this model is
OpenAI’s model page describes GPT-5.6 Luna as a GPT-5.6 model designed for cost-sensitive, high-volume workloads. It roughly corresponds to the nano model tier used in earlier GPT-5 families.
The model supports text and image input with text output. OpenAI’s GPT-5.6 guidance positions Luna as the efficient high-volume option below Terra and Sol.
Pricing notes
The calculator on this page uses OpenAI’s official standard short-context pricing row for gpt-5.6-luna: $1.00 per 1M input tokens and $6.00 per 1M output tokens.
OpenAI’s pricing page also lists cached input at $0.10 per 1M tokens and cache writes at $1.25 per 1M tokens for the standard short-context row. The model page says prompts with more than 272K input tokens are priced at 2x input and 1.5x output for the full request. Those cached, cache-write, and long-context figures are noted here but are not used in the top-level calculator fields.
Benchmarks and specs
OpenAI’s model page lists GPT-5.6 Luna with a 1,050,000-token context window, a 128,000-token maximum output, and a Feb 16, 2026 knowledge cutoff. It also lists reasoning token support.
No benchmark score is shown until an exact benchmark source and model identity are matched to GPT-5.6 Luna.
Best fit
GPT-5.6 Luna is best for high-volume assistants, extraction, classification, routing, lightweight coding support, and repeated agent steps where official OpenAI pricing needs to stay low.
Use Terra or Sol when the task needs a stronger GPT-5.6 tier, especially for complex reasoning, difficult coding, or quality-first analysis.