Compare GLM 5.2 from Z.AI and inclusionAI/Ling-mini-2.0 from InclusionAI on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.
GLM 5.2
inclusionAI/Ling-mini-2.0GLM-5.2 is Z.ai’s flagship model for the era of long-horizon tasks. With a truly usable 1M-token context window, it can handle project-level engineering context, execute long-running tasks more reliably, follow engineering standards more consistently, and complete the full development workflow from requirements to multi-platform deployment in a single task.
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.
Prices are per million tokens. Time to First Token and throughput are rolling averages measured on AIHubMix.
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inclusionAI/Ling-mini-2.0: $0.27/M output tokens; GLM 5.2: $3.94/M. Use the cost calculator above to estimate your own workload.
GLM 5.2 accepts text input and supports thinking, tool calling, function calling and structured outputs; inclusionAI/Ling-mini-2.0 accepts text input and supports tool calling, function calling and structured outputs.
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