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.
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.
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inclusionAI/Ling-mini-2.0: $0.272/M output tokens; GLM 5.2: $2.524/M. Use the cost calculator above to estimate your own workload.
inclusionAI/Ling-mini-2.0: 0.5s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.
GLM 5.2 at 35.9 tok/s and inclusionAI/Ling-mini-2.0 at 8.7 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.
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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