OpenAI: GPT-5.6 Luna Pro: multimodal specs, pricing, and fit

The quick read

OpenAI: GPT-5.6 Luna Pro from openai is a balanced pick (#3): a 1.1M window at $1.00 input / $6.00 output per 1M tokens. It aims for capability headroom without top-tier prices—useful when neither raw cost nor absolute frontier quality is the only constraint.

Spec sheet at a glance

By the numbers: 1.1M context window; multimodal (text, image, and file input); 10 exposed API parameters, including tool calling and structured outputs with reasoning support. Use these to judge fit for agentic, long-context, or structured-output workloads.

Pricing & how it compares

Pricing: $1.00 input / $6.00 output per 1M tokens. Its blended $3.50 is above the top-20 median ($1.40). On AI Hippo the composite board rewards cheap long-context models such as Meta: Llama 4 Scout, so a lower rank here means weaker value-per-token, not weaker capability.

Head-to-head

Its closest board neighbor is Google: Gemini 3.1 Pro Preview Custom Tools (1.0M ctx, $7.00/1M blended). Side by side, OpenAI: GPT-5.6 Luna Pro offers 1.1M ctx at $3.50/1M blended: context is longer and, on blended token price, it is cheaper. Pick between them on whichever axis your workload is bound by.

Where it fits

Best-fit workloads: whole-repo & long-document work, screenshot / PDF / image understanding, tool-calling agents, structured-output pipelines, multi-step reasoning.

Cost in practice & verdict

A representative 100K-input + 20K-output task costs about $0.22 on OpenAI: GPT-5.6 Luna Pro. Verdict: a balanced mid-tier option — good when you want capability headroom without top-tier token prices.

Sources

• AI Hippo unified rankings
• Multi-source token pricing
• OpenRouter models API