Ling-mini-2.0 is a small-sized, high-performance large language model based on the MoE architecture. It has a total of 16 billion parameters, but only activates 1.4 billion parameters per token (non-embedding 789 million), achieving extremely high generation speed. Thanks to the efficient MoE design and large-scale high-quality training data, despite activating only 1.4 billion parameters, Ling-mini-2.0 still demonstrates top-tier performance on downstream tasks comparable to dense LLMs under 10 billion parameters and even larger-scale MoE models.
inclusionAI/Ling-mini-2.0 vs Kimi K3
Compare inclusionAI/Ling-mini-2.0 from InclusionAI and Kimi K3 from Moonshot AI on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.
inclusionAI/Ling-mini-2.0Kimi 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.
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.
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Cost calculator
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FAQ
Which is cheaper: inclusionAI/Ling-mini-2.0, Kimi K3?
inclusionAI/Ling-mini-2.0: $0.27/M output tokens; Kimi K3: $15.00/M. Use the cost calculator above to estimate your own workload.
What inputs and capabilities does each model support?
inclusionAI/Ling-mini-2.0 accepts text input and supports tool calling, function calling and structured outputs; Kimi K3 accepts text, image and video input and supports thinking, function calling and structured outputs.
Can I call inclusionAI/Ling-mini-2.0 and Kimi K3 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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