NVIDIA released Nemotron 3.5 Bolt E4B on October 23. The pitch is a small model tuned for agents: it calls tools, follows instructions, and is small enough for laptops, Jetsons and other edge hardware. The model card's benchmarks are tested on H100s, RTX 5090s and DGX Spark. I wanted to see what happens without any of those.

So I took the official 4-bit GGUF, ran it on a plain 8-vCPU Xeon VM with 16 GB of RAM and no GPU, and built a small voice assistant around it. It listens to a WAV file, picks a tool, calls it, and speaks the answer back. Everything below is from my own runs. I've kept the raw CSVs for every number.

What Bolt E4B actually is

A few facts from the model card and the files themselves, because the name hides some of them:

Architecture: Gemma 4 E4B, post-trained by NVIDIA with reinforcement learning (GRPO via NeMo RL) for tool use, instruction following and multi-turn chat. About 8B total parameters and about 4B "effective" ones.

License: OpenMDW-1.1 on NVIDIA's release.…