Compare Kimi K2 0905 from Moonshot AI and GPT 5.6 Luna from OpenAI on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.
Kimi K2 0905
GPT 5.6 LunaKimi-K2-0905 is a large-scale Mixture of Experts (MoE) language model developed by Moonshot AI, with a total of 1 trillion parameters and 32 billion active parameters per forward pass. It supports long-context inference of up to 256k tokens, an expansion from the previous 128k.
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.
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.
Daily traffic served through AIHubMix — how demand for each model is trending.
Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.
Estimate your monthly bill for the same workload on each model.
Monthly = daily × 30. Discounted rates applied where a promotion is active.
GPT 5.6 Luna: $1.2/M output tokens; Kimi K2 0905: $2.192/M. Use the cost calculator above to estimate your own workload.
Kimi K2 0905: 0.8s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.
Kimi K2 0905 accepts 262,144 and GPT 5.6 Luna accepts 1,050,000 input tokens. Maximum output per request is 262,144 tokens on Kimi K2 0905 and 128,000 tokens on GPT 5.6 Luna.
Kimi K2 0905 at 49.0 tok/s and GPT 5.6 Luna at 47.2 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.
Kimi K2 0905 accepts text input and supports tool calling, function calling and structured outputs; GPT 5.6 Luna accepts text and image input and supports tool calling, thinking and structured outputs.
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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