Kimi K3 vs DeepSeek V4 Pro vs GLM-5.2: Open Trillion-Scale MoE Models Compared on Benchmarks, License, and Serving Cost
MarkTechPost Michal Sutter ● Covered by 5 sources
Three Chinese AI labs released large open-weight Mixture-of-Experts models: Moonshot AI's Kimi K3 (2.8 trillion parameters), DeepSeek V4 Pro (1.6 trillion), and Zhipu AI's GLM-5.2 (744 billion). Kimi K3 scores 57 on the Artificial Analysis Intelligence Index and ranks third overall, while DeepSeek V4 Pro costs $0.04 per task and has weights available immediately under MIT license, whereas K3 remains API-only until July 27, 2026. Teams choosing models must trade off capability, cost (ranging from $0.18 to $3.00 per million input tokens), and availability of downloadable weights for self-hosting.
Why it matters
Three open MoE flagships face off on measured intelligence, MIT versus Modified MIT weights, and real serving cost The post Kimi K3 vs DeepSeek V4 Pro vs GLM-5.2: Open Trillion-Scale MoE Models Compared on Benchmarks, License, and Serving Cost appeared first on MarkTechPost.
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