Unverified50% confidenceFactExact time
The Ngram lookup table only reads a few rows per token and does not need to reside permanently in high-speed memory; after stripping out this table, the 2-bit build of the core model requires only 152GB, leaving nearly 100GB of headroom on a 256GB machine.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/31/2026
First Seen
Valid until: 1/29/2027
Sources
Related Entities
Related Claims
UnverifiedWhen the model loads, it first allocates a full-precision shell of approximately 1.29 GB and then reads in 643 MB of full weights, with peak memory potentially reaching approximately 3,400 MB.77% similarUnverifiedF´核心库编译后仅占数百KB，运行时内存占用可控制在几MB以内76% similarUnverifiedConverting the 8-bit Ngram table to 4-bit can save approximately 100 GB, reducing the model size from approximately 475 GB to approximately 385 GB.76% similarUnverifiedAt the 100 million token scale, the archive occupies 28.8 GB plus a 2.2 GB index on disk, while in-process memory via memory-map is only approximately 28 MB.76% similarUnverifiedThe 2-bit quantized DeepSeek 763B model takes up about 175GB of memory, can run on a 256GB machine and leaves room for the KV cache.76% similar
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