Compare DeepSeek V4 Flash from DeepSeek 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.
DeepSeek V4 FlashinclusionAI/Ling-mini-2.0DeepSeek V4 Flash 0423 is DeepSeek's efficiency-optimized Mixture-of-Experts text model, designed for fast inference and workflows requiring tool use, function calling, and structured outputs. It features 284B total parameters with 13B activated parameters and supports a 1M-token context window with cost-effective pricing.
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: $0.272/M output tokens; DeepSeek V4 Flash: $0.928/M. Use the cost calculator above to estimate your own workload.
DeepSeek V4 Flash accepts text input and supports 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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