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NVIDIA Releases Nemotron 3.5 Bolt E4B, an Open Small Model for Local Agents
NVIDIA released Nemotron 3.5 Bolt E4B, an open small language model built by RL post-training of Google's Gemma 4 E4B without supervised fine-tuning. It has 8B total and 4B effective parameters with 64K context, targeting local voice assistants, game NPCs and robot interfaces on RTX, Jetson and Spark hardware. NVIDIA reports top scores on 15 of 21 benchmarks in its own harness, but Qwen3.5-4B leads on Tau2-Bench and long-context tests. Weights, data and training recipes are public, with the Q4_K
Why it matters: It gives developers a concrete open-weight option for running capable tool-calling agents locally on constrained hardware, with disclosed training methods and honest benchmark weaknesses.
NVIDIANemotronGemma