Open-weight local LLM
Nemotron 3 Nano (4B)
⭐ Mac Mini M4 16GB top pick! NVIDIA's hybrid model — distilled from 9B, keeps 95% of its quality. Hybrid attention + SSM layers = ~80–120 tok/s on Apple Silicon. Blazing fast, minimal RAM. NVIDIA Open Model License.
Laptop ready
6 GB RAM
Q5_K_M
Fast chat on Mac Mini M4 / MacBook
Parameters
4B
Minimum RAM
6 GB
Model size
2.8 GB
Quantization
Q5_K_M
Can Nemotron 3 Nano (4B) run locally?
Nemotron 3 Nano (4B) is a good fit for normal laptops and compact desktops with 8 GB RAM or more.
Search for nvidia-nemotron-3-nano-4b in LM Studio or another GGUF-compatible runtime.
nvidia/NVIDIA-Nemotron-3-Nano-4B-GGUFchatlightspeedreasoning
Install path
01
Check RAM fitMinimum 6 GB RAM. Start with the Q5_K_M quant.02
Load the modelSearch nvidia-nemotron-3-nano-4b in LM Studio.03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.Strengths
- ⭐ Top pick for Mac Mini M4 16GB
- Hybrid architecture (attention + SSM) — very fast on Apple Silicon
- Distilled from 9B — retains most quality at 4B
- Only 2.8 GB download — fits in 6GB RAM
- Exceptional speed/quality ratio for its size
- GGUF available on HuggingFace (nvidia/NVIDIA-Nemotron-3-Nano-4B-GGUF)
Limitations
- Short 4K context window (not suited for long documents)
- NVIDIA Open Model License — not fully open-source
- English only
- Older architecture compared to 2025 models
Best use cases
- Fast chat on Mac Mini M4 / MacBook
- Quick Q&A and summarisation
- Code assistance for short snippets
- Edge and offline applications
- RAG pipelines with short chunks
Capability profile
Technical notes
This model fits these next steps
Hardware fit is based on LocalClaw's RAM tier, model size and quantization metadata. Always leave memory headroom for your OS and runtime.