Best open-source models for post-training

This post analyzes the cost drivers for post-training and serving AI models, focusing on active parameters, total parameters, and KV cache size. It categorizes and recommends open-source models (DeepSeek-V4-Flash, GLM-5.2, Kimi K2.6/K2.7 Code, Nemotron-3-Super-120B, Qwen3 family) based on their cost tiers and suitability for text, vision, and coding-agent use cases. It details how MoE architectures, KV cache compression, and asynchronous RL frameworks impact training and inference costs.