Unverified50% confidenceFactExact time
After quantization, ultra-small models typically require only 1–2 GB of VRAM and can run smoothly on an RTX 3060 or Apple Silicon M-series chips.
1
Sources
50%
Confidence
Long-term
Relevance
9/28/2026
First Seen
Sources
Related Entities
Related Claims
VerifiedDense models at the 30B scale are considered the sweet spot for local deployment, capable of running on Apple Silicon devices such as M2 Ultra (192GB) and M4 Pro (48GB), or on an RTX 4090 (24GB VRAM) with the aid of quantization techniques.80% similarUnverifiedLocal inference is constrained by the user's hardware: a 7B-parameter quantized model (such as the Q4 version of Llama 3 8B) has a file size of approximately 4–5 GB, can reach 20–40 tokens per second on a Mac with an Apple M-series chip, and may drop to 3–5 tokens per second on a laptop with only an integrated GPU and 8 GB of RAM.77% similarUnverifiedOn Apple Silicon, the natively recommended approach is MLX 4-bit affine quantization (group size 64), with a 4-bit MLX build occupying approximately 15 GB of unified memory.77% similarUnverified该1-bit量化的27B模型能够在仅8GB内存的设备上运行74% similarVerifiedThe memory bandwidth of Apple M-series chips can reach 200–800 GB/s (depending on the specific model)72% similar
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