SmolLM2 360M
SmolLM2 360M loads in 0.5 GB at Q4_K_M, comfortably from 8 GB of memory, Macs included, starting at the Mac Mini M6 16GB. Below is the memory math we ran for it, the smallest card that fits, and the fastest machine we track.
How much memory does SmolLM2 360M need?
SmolLM2 360M is a 0.36B dense model built for chat, embedded. The weights alone take 0.5 GB at Q4_K_M; add context and the OS, and it belongs in the 8 GB memory class. Every number below comes from the ModelFit engine: speeds are estimates, labeled est., because we do not benchmark hardware ourselves.
KV = fp16 estimate (q8_0 cache roughly halves it). "Comfortable" = weights + KV within the engine's tiered budget (~70-85% of memory).
Which machines run SmolLM2 360M?
Verdicts come from the same engine that powers our fit checker: memory capacity first, bandwidth for speed. How we compute these numbers · Hugging Face model card
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Frequently asked questions
How much memory does SmolLM2 360M need?
0.5 GB for the Q4_K_M weights, plus ~1.8 GB of KV-cache at 16k context, about 2.3 GB total. Comfortable from 8 GB of VRAM or unified memory.
Does SmolLM2 360M run on a Mac?
Yes, from the Mac Mini M6 16GB (~180 tok/s est.). Unified memory means the RAM budget is the only limit.
What is the smallest GPU for SmolLM2 360M?
The NVIDIA GeForce RTX 4060 (8 GB VRAM) is the smallest tracked card that runs SmolLM2 360M comfortably, ~176 tok/s est.
Cite this page
ModelFit: SmolLM2 360M, specs, memory math and hardware verdicts. https://modelfit.io/models/smollm2-360m/ (dataset updated 2026-10-13, CC BY 4.0).