Text model · LFM
LF LFM2 350M: RAM and VRAM requirements
LFM2 350M needs about 1.4 GB to run at Q4_K_M (the Q4_K_M GGUF file is ~0.45 GB to download; KV cache and overhead add the rest), or about 1.3 GB at Q8_0. The lightest hardware that runs it is Apple M1 (8GB).
LFM family · 0.354B params · released Nov 2025.
Shopping for hardware? See what runs LFM2 350M →
Q4_K_M and Q8_0 are GGUF download (file) sizes. Memory @ Q4 includes the KV cache and overhead, so it runs larger than the file on disk.
Will it run on your device?
LFM2 350M runs on 40 of 40 tracked devices at Q4_K_M.
Memory breakdown
How context length changes it
LFM2 350M is small enough that the context window is the thing to size for: 128k needs ~5.9 GB versus ~1.4 GB at 4k, so pick the window you actually use.
Speed drops too: every token re-reads the KV cache, so at 128k context LFM2 350M generates at roughly ~9% of its short-context speed. How this is estimated.
Quantization sizes
| Quantization | Size on disk |
|---|---|
| Q2_K | 0.1 GB est |
| Q3_K_M | 0.2 GB est |
| Q4_K_M (default) | 0.45 GB |
| Q5_K_M | 0.3 GB est |
| Q6_K | 0.3 GB est |
| Q8_0 | 0.35 GB |
| FP16 | 0.711 GB |
Lower quant = smaller and faster, slightly lower quality. Q4_K_M is the common default.
Run it
llama-cli -hf LiquidAI/LFM2-350M-GGUF:Q4_K_M lms get LiquidAI/LFM2-350M-GGUF Which devices can run LFM2 350M?
Apple Silicon Macs
- Apple M1 (8GB) Yes
- Apple M2 (16GB) Yes
- Apple M4 (16GB) Yes
- Apple M5 (16GB) Yes
- Apple M3 Pro (18GB) Yes
- Apple M4 (24GB) Yes
- Apple M4 Pro (24GB) Yes
- Apple M5 (32GB) Yes
- Apple M4 Pro (48GB) Yes
- Apple M5 Pro (48GB) Yes
- Apple M4 Max (64GB) Yes
- Apple M4 Max (128GB) Yes
- Apple M5 Max (128GB) Yes
- Apple M3 Ultra (256GB) Yes
RAM-only laptops
iPhone & iPad
Android
NVIDIA GPUs
Same job, different size
Pick by what fits your memory: step down to free up VRAM, or step up if you have headroom.
Similar models
Head-to-head
FAQ
How much VRAM or RAM does LFM2 350M need?
At Q4_K_M, LFM2 350M needs about 1.4 GB (weights ~0.45 GB + KV cache + overhead) at a 4k context. At Q8_0 budget ~1.3 GB.
What is the Q4_K_M GGUF file size of LFM2 350M?
The Q4_K_M GGUF file is about 0.45 GB to download, and the Q8_0 GGUF is about 0.35 GB. That is the weights file on disk; to run it you also need room for the KV cache and overhead, so budget ~1.4 GB of memory at Q4_K_M.
Can LFM2 350M run on a laptop?
Yes, LFM2 350M fits on a 16 GB machine at Q4_K_M and runs on Apple Silicon or a 12 GB+ GPU comfortably.
Can I use LFM2 350M commercially?
Conditionally. LFM Open License: free under $10M revenue; larger companies need a commercial license.
Understand the numbers
Short guides to the ideas behind LFM2 350M's memory and quant figures.
Exact params: 354,483,968. Hybrid architecture: 10 double-gated short-range LIV convolution blocks + 6 GQA blocks. Context 128K from config.json max_position_embeddings. LFM Open License: free for academic/research and companies with revenue under $10M; larger enterprises must license commercially. No official ollama.com/library tag; community sam860/LFM2:350m exists. Paper arXiv:2511.23404 released November 2025. Q4_K_M 229 MB is the standard (non-hip-optimized) file.
Sources
Last validated 2026-08-03. Memory figures are estimates. See methodology.