Model: Nemotron 3.5 Bolt E4B

NVIDIA's Nemotron 3.5 Bolt E4B is a small vision model built on Google's Gemma 4 E4B. It has the same 42-layer shape, about 4.7B parameters doing the work plus a 2.8B per-layer embedding table, with image input and a 64K window. Only 4 of its 42 layers keep a cache that grows with context, so long context is cheap. The one plain Q4_K_M file (LM Studio's, 6.2 GB) is much larger than the level name suggests, because the embedding table is not stored at 4 bits. It needs about 6.6 GB at 4K, comfortable on an 8 GB card, and 7.6 GB at 64K, tight on an 8 GB card. Q8_0 (an 8.0 GB file) needs about 8.5 GB at 4K and wants a 12 GB card. On a discrete card llama.cpp keeps the embedding table in system RAM, so real VRAM use is lower than shown. The vision encoder is a separate 0.6–1.0 GB file published by unsloth, and a small DFlash draft model for speculative decoding ships beside it. NVIDIA's benchmark claims are its own, and no per-level quality loss has been published.