OpenAI: GPT-6 Luna Pro (batch): multimodal specs, pricing, and fit
OpenAI: GPT-6 Luna Pro (batch) ranks #7 on the AI Hippo board with a 1.1M context window and $0.05 input / $0.25 output per 1M tokens. Specs, cost math, and how it compares.
The quick read
OpenAI: GPT-6 Luna Pro (batch) from openai is a balanced pick (#7): a 1.1M window at $0.05 input / $0.25 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); 9 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: $0.05 input / $0.25 output per 1M tokens. Its blended $0.15 is at or below the top-20 median ($0.34). 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 Xiaomi: MiMo-V2.5 (1.1M ctx, $0.21/1M blended). Side by side, OpenAI: GPT-6 Luna Pro (batch) offers 1.1M ctx at $0.15/1M blended: context is similar 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, high-volume, cost-sensitive batch.
Cost in practice & verdict
A representative 100K-input + 20K-output task costs about $0.01 on OpenAI: GPT-6 Luna Pro (batch). Verdict: strong price-performance for a default, high-volume workhorse where every token counts.