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DeepSeek, Qwen, Kimi, or GLM: A CTO's Cost-Driven Guide to Chinese LLMs

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A CTO facing unsustainable cloud inference costs spent several months testing four major Chinese large language model families — DeepSeek, Qwen, Kimi, and GLM — as alternatives to Western providers. Pricing varies dramatically across the group, with Qwen and GLM offering entry-level models as cheap as $0.01 per million tokens, while Kimi starts at $3.00 per million with no budget tier. DeepSeek stood out for code generation and speed, Kimi led on multi-step reasoning, and Qwen offered the broadest multimodal support among the four. All four families expose OpenAI-compatible APIs, which significantly lowers the cost of switching or running workloads in parallel. The author argues that at scale — say, 500 million tokens per month — even a $0.10 per million token difference between providers can translate into $50,000 in avoidable spending.

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