Hardcore Test: Running Kimi K3 Locally Across Dual Clusters via RPC
segmond · reddit · 2026-08-09
A Reddit user shared their hardcore practice of running the Kimi K3 model locally. Because a single machine's VRAM is insufficient to fully load the model, the author utilized llama.cpp via RPC protocol for distributed inference across two compute clusters, with the main cluster still partially offloading to system RAM.
The author is currently running the IQ1M quantized version, aiming to upgrade to Q2KXL eventually. They plan to consolidate all GPUs into a single system to eliminate RPC overhead, expecting a 2-3x speedup. Strategically, they intend to use the large model for task planning and farm out the actual coding work to smaller, faster models like DeepSeek and Qwen, showcasing a hardcore local compute approach and agentic scheduling.
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