GPT-5.6 Luna is designed for cost-sensitive, high-volume workloads. It roughly corresponds to the nano model tier used in earlier GPT-5 families.
GPT 5.6 Luna vs Mai Image 2.6
Compare GPT 5.6 Luna from OpenAI and Mai Image 2.6 from Microsoft on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.
MAI-Image-2.6 is Microsoft's latest image-generation and editing model. It can generate images from text prompts and supports image-guided editing in multiple aspect ratios.
Pricing & Specifications
Prices are per million tokens. Time to First Token and throughput are rolling averages measured on AIHubMix.
Promotional prices show the discounted rate; see each model page for promotion windows.
Activity Past 30 Days
Daily traffic served through AIHubMix — how demand for each model is trending.
Tokens / day
Requests / day
Performance Past 3 Days
Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.
Throughput (tok/s)
TTFT (s)
Uptime (%)
Cost calculator
Estimate your monthly bill for the same workload on each model.
Monthly = daily × 30. Discounted rates applied where a promotion is active.
FAQ
Which is cheaper: GPT 5.6 Luna, Mai Image 2.6?
Mai Image 2.6: $5/M output tokens; GPT 5.6 Luna: $6/M. Use the cost calculator above to estimate your own workload.
How large is each context window?
GPT 5.6 Luna accepts 1,050,000 and Mai Image 2.6 accepts 32,000 input tokens. Maximum output per request is 128,000 tokens on GPT 5.6 Luna and 4,096 tokens on Mai Image 2.6.
What inputs and capabilities does each model support?
GPT 5.6 Luna accepts text and image input and supports tool calling, thinking and structured outputs; Mai Image 2.6 accepts text and image input.
Can I call GPT 5.6 Luna and Mai Image 2.6 with the same API key?
Yes. AIHubMix serves every model on this page behind one OpenAI-compatible endpoint, so switching between them is a one-line change to the model field — no second account, key or SDK.
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