What are the hardware requirements for Nemotron Cascade 8B Thinking?

Nemotron Cascade 8B Thinking requires approximately 16.3 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Nemotron Cascade 8B Thinking and how large is it?

Nemotron Cascade 8B Thinking is developed by nvidia, a model with 8b 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 Cascade 8B Thinking?

Nemotron Cascade 8B Thinking is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Nemotron Cascade 8B Thinking by nvidia — VRAM 16.3GB, 32K context

Name: Nemotron Cascade 8B Thinking
Author: nvidia

Nemotron Cascade 8B Thinking is an open-source language model by nvidia. Features: 8b LLM, VRAM: 16.3GB, Context: 32K, License: other, LLM Explorer Score: 0.23.

Arxiv:2309.00071 Arxiv:2512.13607 Conversational En Endpoints compatible General-purpose Nemotron-cascade Nvidia Pytorch Qwen3 Reasoning Region:us Rl Safetensors Sft Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/nvidia/Nemotron-Cascade-8B-Thinking

Nemotron Cascade 8B Thinking Parameters and Internals

LLM Name	Nemotron Cascade 8B Thinking
Repository 🤗	https://huggingface.co/nvidia/Nemotron-Cascade-8B-Thinking
Model Size	8b
Required VRAM	16.3 GB
Updated	2026-07-19
Maintainer	nvidia
Model Type	qwen3
Model Files	4.8 GB: 1-of-4 5.0 GB: 2-of-4 4.9 GB: 3-of-4 1.6 GB: 4-of-4
Supported Languages	en
Model Architecture	Qwen3ForCausalLM
License	other
Context Length	32768
Model Max Length	32768
Transformers Version	4.51.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Nemotron Cascade 8B Thinking 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

Best Alternatives to Nemotron Cascade 8B Thinking

Best Alternatives	Context / RAM	Downloads	Likes
PaCoRe 8B	320K / 1.2 GB	54	48
RLVR 8B 0926	320K / 1.2 GB	63	8
...n3 8B 320K Context 10X Massive	320K / 16.4 GB	20	0
...r Of Horror Jan V1 256K Ctx 8B	256K / 16.1 GB	33	3
... BIG Jan Horror V1 256K Ctx 8B	256K / 16.1 GB	44	0
Qwen3 8B 256K Context 8X Grand	256K / 16.4 GB	95	0
...wen3 8B 192K Context 6X Larger	192K / 16.4 GB	55	0
DeepSeek R1 0528 Qwen3 8B	128K / 16.4 GB	1762293	1082
...Reason 8B Pretrain Competition	128K / 16.8 GB	244	0
Marco DeepResearch 8B	128K / 16.3 GB	520	27

Note: green Score (e.g. "73.2") means that the model is better than nvidia/Nemotron-Cascade-8B-Thinking.