text model · Nemotron 3 · Windows
Can I run Nemotron 3 Nano 4B on Nvidia GeForce RTX 4060 Ti (16GB)?
Yes. Nemotron 3 Nano 4B runs on Nvidia GeForce RTX 4060 Ti (16GB) at Q4_K_M (~3.9 GB of ~15 GB usable).
Runs at Q4_K_M using ~3.9 GB of ~15 GB usable. You have room for FP16 for higher quality.
That figure is at a 4k context and moves about ±15% as context length changes. Nvidia GeForce RTX 4060 Ti (16GB) leaves ~11.1 GB of headroom, room to step up to FP16 for higher quality.
- Q4_K_M needed
- ~3.9 GB
- Usable on device
- ~15 GB
- Device memory
- 16 GB
- Best quant
- Q4_K_M
Which quant fits
Running cost · estimate
- Power draw
- ~165 W
- Electricity / 1M tokens
- ~$0.1
- Pays for itself after
- ~1,248M tok
At ~$0.15/kWh and the estimated ~71 tok/s, a million generated tokens costs about $0.1 in electricity. Versus a hosted API at ~$0.5 per million tokens, the ~$499 Nvidia GeForce RTX 4060 Ti (16GB) pays for itself after roughly 1,248 million tokens, so local hardware is mostly a fixed cost, not a per-token one. TDP is the peak draw, so this is an upper bound. Assumptions.
Run it
Pick your tool. All 3 load the same Q4_K_M weights.
ollama run nemotron-3-nano:4b llama-cli -hf nvidia/NVIDIA-Nemotron-3-Nano-4B-GGUF:Q4_K_M lms get nvidia/NVIDIA-Nemotron-3-Nano-4B-GGUF - Parameters
- 4B
- Q4_K_M size
- 2.64 GB
- Q8_0 size
- 3.94 GB
- Context
- 256k
- Ollama tag
- nemotron-3-nano:4b
- Memory
- 16 GB vram
- Usable for weights
- ~15 GB
- Power draw
- ~165 W
- Best runtime
- Ollama (CUDA) / llama.cpp CUDA
You could also run
Run Nemotron 3 Nano 4B on other hardware
FAQ
Can Nvidia GeForce RTX 4060 Ti (16GB) run Nemotron 3 Nano 4B?
Yes. Nemotron 3 Nano 4B runs on Nvidia GeForce RTX 4060 Ti (16GB) at Q4_K_M (~3.9 GB of ~15 GB usable).
How much memory does Nemotron 3 Nano 4B need?
Nvidia GeForce RTX 4060 Ti (16GB) has room to spare. At Q4_K_M the weights are ~2.64 GB; with KV cache and runtime overhead, budget ~3.9 GB at a 4k context.
What is the best tool to run Nemotron 3 Nano 4B 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
A live badge for your model card or README, updated as the data is. [](https://localmodel.run/can-i-run/nemotron-3-nano-4b/nvidia-rtx-4060-ti-16gb) 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.