Can I run it?

Can I run LFM2.5 2.6B on Apple M4?

Runs great

Runs great fully in unified memory on your Apple M4 at BF16, 8K context, about 11–15 tok/s. Weights 5.03 GB plus 0.47 GB of KV cache — 5.85 GB of 11.0 GB usable. Up to 64K context still fits.

Best quantBF16

Working context8K

Max that fits64K

Speed11–15 tok/s

Weights5.03 GB

KV cache0.47 GB

Total5.85 GB

Usable11.0 GB

LFM2.5 2.6B details · Apple M4 page · How this estimate is made

Run commands

llama.cpp

llama-server -hf LiquidAI/LFM2.5-2.6B-GGUF:BF16 -c 8192 -ngl 30

Ollama

ollama run lfm2.5

LM Studio

lms get LiquidAI/LFM2.5-2.6B-GGUF
# Then load quant BF16

Assumptions

Estimate, not a benchmark. Decode speed uses a memory-bandwidth model at 55–75% of peak.
KV cache is FP16. Engine overhead assumes llama.cpp (0.3 GB + 1% of the weights). Ollama is closer to 0.9 GB + 3%, LM Studio closer to 1 GB + 3%.
BF16 size is the real GGUF file size from Hugging Face.
Unified memory uses 75% for the GPU by default, and always leaves about 5 GB for the OS.
Speed is quoted at 8K context, not at the maximum context that still fits.

Larger models that also fit

Can I run Qwen3.8 27B on Apple M4? — Tight fit, UD-Q2_K_XL, 6.4–8.7 tok/s
Can I run gemma 4 12b it on Apple M4? — Tight fit, Q6_K, 5.1–6.9 tok/s
Can I run Qwen3.5 9B on Apple M4? — Tight fit, Q8_0, 6.7–9.2 tok/s

Updated 2026-10-24. Profile on this page is the device default.