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Yes. SmolLM2 135M fits in fast memory on M3 8GB at FP16 (0.9 GB needed, 5.4 GB usable), about 296 tok/s (estimate).
Hardware: M3 8GB · Model: SmolLM2 135M
M3 8GB has 8 GB of unified memory and 100 GB/s of memory bandwidth. M2 8GB has the same memory and bandwidth, so the fit numbers match; this page is M3 8GB. The checker leaves macOS a share of unified memory, so Ollama can use 5.4 GB. SmolLM2 135M (0.135B, HuggingFace) at FP16 is a 0.27 GB download and needs 0.9 GB with headroom for about 8k tokens.
| Best quant | FP16 |
|---|---|
| Download size | 0.27 GB |
| Memory needed | 0.9 GB |
| Usable fast memory | 5.4 GB |
| Fit | fits in fast memory |
| Estimated speed | ~296 tok/s (estimate) |
| Command | ollama run smollm2:135m |
Estimates, not benchmarks. Model sizes are ollama.com download sizes; memory needed adds headroom for ~8k tokens of context; speeds are rough figures from memory bandwidth. Data updated 2026-10-23.
A project by OnDevice Labs · llms.txt