OPEN LINK ↗
// 1h agoMODEL RELEASE
NVIDIA Nemotron 3.5 Bolt E4B Hits 4GB
NVIDIA released an open 8B-parameter model with 4B effective parameters, post-trained from Gemma 4 E4B to fit conversational agents into roughly 4GB. It targets local voice assistants, interactive characters, embedded devices, and multi-turn tool use with 64K context.
// ANALYSIS
This is a compelling edge-model release, but the “vision” framing appears overstated: NVIDIA’s official materials describe Bolt E4B as a small language model, not a multimodal vision model.
- –~4GB target memory makes capable local agents more practical on constrained hardware
- –Strong gains in tool use, grounding, instruction following, and conversational brevity
- –GGUF availability through Unsloth, llama.cpp, Ollama, and LM Studio lowers deployment friction
- –64K context and configurable reasoning suit persistent device assistants and embedded workflows
- –Developers should benchmark latency, thermals, and quantized quality on actual phones before assuming broad 6GB-RAM support
// TAGS
nemotron-3.5-bolt-e4bllmsmall-llmopen-weightsquantizationedge-aitool-uselocal-first
DISCOVERED
1h ago
2026-10-23
PUBLISHED
2h ago
2026-10-23
RELEVANCE
9/ 10
AUTHOR
0x0SojalSec