What are the hardware requirements for Nemotron 3.5 Bolt 74B A9B AutoRound W4A16 G128 Sym?

Nemotron 3.5 Bolt 74B A9B AutoRound W4A16 G128 Sym requires approximately 42.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Nemotron 3.5 Bolt 74B A9B AutoRound W4A16 G128 Sym and how large is it?

Nemotron 3.5 Bolt 74B A9B AutoRound W4A16 G128 Sym is developed by SergiioB, a model with 74b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Nemotron 3.5 Bolt 74B A9B AutoRound W4A16 G128 Sym?

Nemotron 3.5 Bolt 74B A9B AutoRound W4A16 G128 Sym is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Nemotron 3.5 Bolt 74B A9B AutoRound W4A16 G128 Sym by SergiioB — VRAM 42.2GB

Name: Nemotron 3.5 Bolt 74B A9B AutoRound W4A16 G128 Sym
Author: SergiioB

Nemotron 3.5 Bolt 74B A9B AutoRound W4A16 G128 Sym is an open-source language model by SergiioB. Features: 74b LLM, VRAM: 42.2GB, License: other, LLM Explorer Score: 0.3.

4-bit Arc-pro-b70 Autoround Base model:nvidia/nvidia-nemot... Base model:quantized:nvidia/nv... Conversational Custom code De En Endpoints compatible Es Fr Gptq Image-text-to-text Int4 Intel It Ja Nemotron-3.5 Nemotron h omni Quantized Region:us Safetensors Sharded Tensorflow Vllm W4a16 Xpu

Model Card on HF 🤗: https://huggingface.co/SergiioB/Nemotron-3.5-Bolt-74B-A9B-AutoRound-W4A16-G128-sym

Nemotron 3.5 Bolt 74B A9B AutoRound W4A16 G128 Sym Parameters and Internals

LLM Name	Nemotron 3.5 Bolt 74B A9B AutoRound W4A16 G128 Sym
Repository 🤗	https://huggingface.co/SergiioB/Nemotron-3.5-Bolt-74B-A9B-AutoRound-W4A16-G128-sym
Base Model(s)	nvidia/NVIDIA-Nemotron-3.5-Bolt-74B-A9B-BF16 nvidia/NVIDIA-Nemotron-3.5-Bolt-74B-A9B-BF16
Model Size	74b
Required VRAM	42.2 GB
Updated	2026-10-21
Maintainer	SergiioB
Model Type	nemotron_h_omni
Model Files	5.4 GB: 1-of-8 5.4 GB: 2-of-8 5.4 GB: 3-of-8 5.4 GB: 4-of-8 5.4 GB: 5-of-8 5.4 GB: 6-of-8 5.4 GB: 7-of-8 4.4 GB: 8-of-8 1.7 GB
Supported Languages	en es fr de it ja
Model Architecture	NemotronH_Omni_Reasoning_V3
License	other
Model Max Length	262144
Transformers Version	5.12.1
Tokenizer Class	TokenizersBackend
Padding Token	<\|im_end\|>
Torch Data Type	float16

Rank the Nemotron 3.5 Bolt 74B A9B AutoRound W4A16 G128 Sym capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

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Note: green Score (e.g. "73.2") means that the model is better than SergiioB/Nemotron-3.5-Bolt-74B-A9B-AutoRound-W4A16-G128-sym.