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Kimi K3 model runs on CPU with 8GB RAM via custom C99 engine

A developer has created a C99 inference engine that allows the Kimi K3 model to run on a single CPU with 8 GB of RAM. While not practical for production due to slow speeds (around 33 seconds per token at the lowest RAM setting), the engine was built for understanding the model's architecture. The implementation bypasses traditional frameworks and GPUs, relying solely on CPU processing and NVMe storage for the model's large checkpoint. AI

IMPACT Demonstrates novel ways to run large models on limited hardware, potentially lowering accessibility barriers.

RANK_REASON Custom inference engine for an existing model, not a new model release or significant research.

Read on r/LocalLLaMA →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Kimi K3 model runs on CPU with 8GB RAM via custom C99 engine

COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/FareedKhan557 ·

    I pushed Kimi K3 onto one CPU with 8 GB of RAM

    <!-- SC_OFF --><div class="md"><p>I <a href="https://www.hyperstack.cloud/technical-resources/tutorials/deploy-kimi-k3-on-gpu-cloud-for-multi-node-2.8t-inference">deployed K3 on 32 H100s at work</a> a couple of weeks ago and <strong>then got annoyed that there was no way to poke …