Kimi K3 is Kimi’s flagship model for long-horizon coding and end-to-end knowledge work, with a 1M-token context window and industry-leading intelligence.
Kimi K3 vs Nemotron Nano 9B V2 (free)
Compare Kimi K3 from Moonshot AI and Nemotron Nano 9B V2 (free) from Nvidia on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.
NVIDIA-Nemotron-Nano-9B-v2-free is a large language model trained from scratch by NVIDIA. Designed as a unified model, it efficiently handles both reasoning and non-reasoning tasks to respond to a wide range of user queries. With a generous context length of 128,000 tokens, it is highly capable of processing long and complex documents.
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
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Performance Past 3 Days
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Throughput (tok/s)
TTFT (s)
Uptime (%)
Cost calculator
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Monthly = daily × 30. Discounted rates applied where a promotion is active.
FAQ
How large is each context window?
Kimi K3 accepts 1,048,576 and Nemotron Nano 9B V2 (free) accepts 128,000 input tokens.
What inputs and capabilities does each model support?
Kimi K3 accepts text, image and video input and supports thinking, function calling and structured outputs; Nemotron Nano 9B V2 (free) accepts text input and supports reasoning, tool calling and long context.
Can I call Kimi K3 and Nemotron Nano 9B V2 (free) 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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