Unverified60% confidenceFactExact time
Ternary representation theoretically requires only about 1.58 bits per parameter, which can yield nearly a 10x storage compression compared to FP16.
2
Sources
60%
Confidence
Long-term
Relevance
8/5/2026
First Seen
Sources
Related Claims
Verified4-bit quantization compresses each parameter to 0.5 bytes, theoretically compressing 140GB down to approximately 35–40GB.78% similarUnverifiedQuantization can compress the storage size of a 70-billion-parameter model from approximately 140 GB in FP16 to approximately 35–40 GB in INT4, enabling it to run on consumer-grade hardware such as a single RTX 4090 with CPU memory offloading.77% similarUnverifiedParquet列式存储压缩比通常达行式格式的3-10倍75% similarVerifiedThe model weights alone of a 175-billion-parameter model (in BF16 precision) require 350 GB of storage, and the Adam optimizer must maintain two sets of states—first-order moments and second-order moments—totaling more than 1 TB.75% similar
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