Unverified50% confidenceFactExact time
IQ2_XS can compress a model to close to 2 bits/weight, enabling a 70B model that would otherwise require 48 GB of VRAM to fit into a 24 GB consumer-grade GPU
1
Sources
50%
Confidence
Long-term
Relevance
8/14/2026
First Seen
Sources
看懂GGUF量化：Q4_K_M与Q4_K_S的真正区别
Related Claims
UnverifiedEven compressing the weights to 214GB using 4-bit quantization still far exceeds the capacity of a single 48GB GPU.77% similarVerifiedA 30B parameter model that originally required 60 GB of VRAM can run on consumer-grade GPUs with 16 GB or even 8 GB of VRAM after quantization.75% similarUnverifiedINT4 quantized models are expected to complete on GPUs with 8 GB or even less VRAM the model inference that originally required 16 GB or 24 GB of VRAM.75% similarVerified32B参数规模的模型在量化后通常可以压缩到约16-20GB显存占用，一张NVIDIA RTX 4090（24GB显存）就能运行74% similarUnverifiedA 70B model can be compressed to approximately 35GB at INT4 precision.73% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/745190API
curl https://kongchang.com/api/v1/knowledge/claims/745190MCP
get_claim(id=745190)