Unverified50% confidenceFactExact time
For actually deploying Hy-Memory-30B-A3B, the realistic bar is a 24 GB GPU or 32 GB Mac running Q4_K_M, while going to Q8_0 with long context requires 64 GB.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/17/2026
First Seen
Valid until: 1/15/2027
Sources
Related Entities
Related Claims
VerifiedEven compressing the weights to 214GB using 4-bit quantization still far exceeds the capacity of a single 48GB GPU.77% similarVerifiedAfter 4-bit quantization, Llama 3.3 70B has a model size of approximately 40 GB and can run on a Mac Studio with 64 GB of memory or a single professional GPU with 48 GB of VRAM.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.77% similarUnverifiedAround 36 GB of RAM is recommended for the Q2 version, while 64 GB or more (with weights larger than 43 GB) allows for higher-precision versions.76% similarVerifiedA 35B model requires approximately 70GB of VRAM at FP16 precision, far exceeding the RTX 5090's 32GB capacity, so single-GPU deployment requires quantization.76% similar
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