text model · LFM · Windows
Can I run LFM2 24B-A2B on Nvidia GeForce RTX 3060 (12GB)?
No. LFM2 24B-A2B needs ~15.4 GB even at Q4_K_M, but Nvidia GeForce RTX 3060 (12GB) only has ~11 GB usable.
Needs ~15.4 GB even at Q4_K_M, but only ~11 GB is usable.
That figure is at a 4k context and moves about ±15% as context length changes.
The gap is about 4.4 GB: LFM2 24B-A2B needs roughly 15.4 GB at Q4_K_M and Nvidia GeForce RTX 3060 (12GB) leaves only about 11 GB usable for a model. The lightest tracked hardware that runs LFM2 24B-A2B is the Apple M4 (24GB) at 24 GB. See LFM2 24B-A2B on Apple M4 (24GB).
- Q4_K_M needed
- ~15.4 GB
- Usable on device
- ~11 GB
- Device memory
- 12 GB
Which quant fits
- Parameters
- 24B (MoE, 2.3B active)
- Q4_K_M size
- 13.43 GB
- Q8_0 size
- 23.61 GB
- Context
- 32k
- Ollama tag
- lfm2:24b
- Memory
- 12 GB vram
- Usable for weights
- ~11 GB
- Power draw
- ~170 W
- Best runtime
- Ollama (CUDA) / llama.cpp CUDA
What you can run instead
Run LFM2 24B-A2B on other hardware
FAQ
Can Nvidia GeForce RTX 3060 (12GB) run LFM2 24B-A2B?
No. LFM2 24B-A2B needs ~15.4 GB even at Q4_K_M, but Nvidia GeForce RTX 3060 (12GB) only has ~11 GB usable.
How much memory does LFM2 24B-A2B need?
Nvidia GeForce RTX 3060 (12GB) does not have enough memory. At Q4_K_M the weights are ~13.43 GB; with KV cache and runtime overhead, budget ~15.4 GB at a 4k context. It is a Mixture-of-Experts model (24B total / 2.3B active), so all experts must stay in memory; memory tracks total params, not active params.
What is the best tool to run LFM2 24B-A2B on Windows?
LM Studio for a simple setup; Ollama (CUDA) for the most speed. AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.
Embed this
[](https://localmodel.run/can-i-run/lfm2-24b-a2b/nvidia-rtx-3060-12gb) Sources
Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.