NVIDIA releases Nemotron 3.5 Bolt E4B for local agents in about 4GB of VRAM
NVIDIA took Gemma 4 E4B and post-trained it with reinforcement learning alone, giving a 4B-effective model with 64K context tuned for tool calls and short conversational turns. Quantized builds fit in roughly 4GB, aimed at RTX cards and Jetson, and it ships under OpenMDW-1.1 on Hugging Face and Ollama. Qwen3.5-4B still beats it on some agent benchmarks.
Why it matters
An openly licensed tool-using model that runs on consumer GPUs and edge boards without cloud calls.