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Kimi K3 model quantized to 1.1 TB GGUF format on CPU

By PulseAugur Editorial · [1 sources] ·

A team has successfully quantized the Kimi K3 model, a 2.8 trillion parameter model, into the GGUF format. They achieved a Q3_K_S quantization, resulting in a file size of 1.1 TB. This process was performed on CPU-only hardware, utilizing 1.5 TB of RAM and 110 threads, demonstrating the feasibility of running large models without dedicated GPUs. AI

IMPACT Demonstrates feasibility of running massive models on consumer-grade hardware, potentially lowering barriers to entry for advanced AI research.

RANK_REASON The item details the process and results of quantizing a large language model, which falls under research and development in AI. [lever_c_demoted from research: ic=1 ai=1.0]

Read on r/LocalLLaMA →

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

Kimi K3 model quantized to 1.1 TB GGUF format on CPU

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0 / 100
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The item details the process and results of quantizing a large language model, which falls under research and development in AI. [lever_c_demoted from research: ic=1 ai=1.0]
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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model release, infra
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High
Clearly on-topic for AI-industry coverage.
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58 days old
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COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/Fun-Meaning-6474 ·

    Quantizing Kimi K3 (2.8T A50B) to GGUF ourselves - Q3_K_S works, 1.1 TB on disk

    <table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1vaaqdl/quantizing_kimi_k3_28t_a50b_to_gguf_ourselves_q3/"> <img alt="Quantizing Kimi K3 (2.8T A50B) to GGUF ourselves - Q3_K_S works, 1.1 TB on disk" src="https://preview.redd.it/bd7jqhj6s8gh1.png?width=140&a…

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