Nemotron 3.5 Bolt E4B Q4_K_M
on Mac, M4 Pro, 48 GB

Fits with about 40 GB to spare. Finished 7 of 15 runs inside a 600 token limit.

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Run history

Every run

Date	Speed	Memory
30 October 2026	52.1 t/s	7.5 GB

Change over time

How each figure moved, from the earliest run in each period to the latest.

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Against the maker's claim

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How we measured

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curl -fsSL https://onticpost.com/run.sh | sh -s -- \ --model MODEL --runs 6

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About Nemotron 3.5 Bolt E4B Q4_K_M

What is Nemotron 3.5 Bolt E4B?

Nemotron 3.5 Bolt E4B is a small language model that NVIDIA post trained from Google’s Gemma 4 E4B, aimed at fast local voice and device assistants. This entry measures the Q4_K_M build, a 6.18 GB file, in LM Studio on a Mac with an M4 Pro chip and 48 GB of memory.

What was measured

Fifteen runs across five tasks in LM Studio, llama.cpp Metal runtime 2.47.0, context 65,536 tokens, 600 tokens allowed per run, on macOS 27.0.1. Writing speed is the middle run. Memory is the larger of the readings taken before and after the runs. 7 of the 15 runs finished inside the allowance. In 8 the limit cut the answer off part way.

Other figures

Measure	Result
Slowest and fastest run	47.95 and 54.13 tokens a second
Wait for the first token, short prompt	0.21 seconds
Wait for the first token, 3,804 token prompt	7.1 seconds
Runs that finished inside 600 tokens	7 of 15
Runs with no answer inside 600 tokens	0 of 15
Model file on disk	6.18 GB

Measured with the same script as every other entry on this machine.

Sources

NVIDIA's Nemotron 3.5 Bolt E4B model card

Cite this page

Hill. "Nemotron 3.5 Bolt E4B Q4_K_M". Onticpost, published 3 November 2026, updated 31 October 2026. https://onticpost.com/index/nemotron-3-5-bolt-e4b-m4-pro-48gb/

Updated 31 October 2026. This address stays the same when the piece is updated.

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