Can I Run LFM2.5-2.6B (free) on a Apple M3 Pro (18GB)?
Runs at full precision (fp16). Zero quality loss.
5 quantizations fit your 18.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| fp16BEST | 6.2 GB | 7.7 GB | 5.2 GB | +11.8 GB |
| Q8_0 | 3.8 GB | 5.3 GB | 2.8 GB | +14.2 GB |
| Q6_K | 3.1 GB | 4.6 GB | 2.1 GB | +14.9 GB |
| Q5_K_M | 2.9 GB | 4.3 GB | 1.9 GB | +15.2 GB |
| Q4_K_M | 2.6 GB | 4.1 GB | 1.6 GB | +15.4 GB |
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All quant variants, benchmark scores, and use-case tags.
Top-ranked open-source models that fit in 18.0GB.
FAQ
Can the Apple M3 Pro (18GB) run LFM2.5-2.6B (free)?
Yes. The Apple M3 Pro (18GB)'s 18.0GB of unified memory is enough to run LFM2.5-2.6B (free) at fp16 quantization (6.2GB required).
What's the best quantization to use?
fp16 is the highest-precision quantization that fits in your 18.0GB. It uses about 6.2GB of memory and 7.7GB recommended for comfortable inference.
What if I need more headroom for context length?
KV cache memory grows with context length. The numbers above assume a baseline 2K-4K context. For long-context use (32K+), add another 2-6GB depending on the model architecture.