Verified65% confidenceFactExact time
After applying INT4 quantization, the memory footprint of a 3B parameter model can be reduced to approximately 2 GB.
3
Sources
65%
Confidence
Long-term
Relevance
9/8/2026
First Seen
Sources
Related Entities
Related Claims
Verified4-bit quantization (such as Q4_K_M) can typically compress the memory footprint of a 3B model from approximately 6GB to approximately 2GB, with a precision loss of less than 2–3%.80% similarVerifiedA 7B-parameter model requires only approximately 4 GB of VRAM to run after 4-bit quantization.77% similarUnverifiedA model with 2B parameters typically requires only about 1–2 GB of memory after INT4 quantization, enabling it to run on mainstream smartphones, embedded development boards, and similar devices.77% similarUnverifiedModels with 2B parameters can run on a single consumer-grade GPU or even a high-performance CPU during inference, with memory usage typically not exceeding 2GB after INT4 quantization.77% similarUnverifiedUsing INT4 quantization technology can reduce the size of a 20B model from approximately 40 GB to approximately 10 GB.76% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/877285API
curl https://kongchang.com/api/v1/knowledge/claims/877285MCP
get_claim(id=877285)