What are the hardware requirements for Qwen3 4B NexusPrime?

Qwen3 4B NexusPrime requires approximately 8.2 GB of VRAM and supports a context window of 40K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3 4B NexusPrime and how large is it?

Qwen3 4B NexusPrime is developed by ZeroXClem, a model with 4b 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 Qwen3 4B NexusPrime?

Qwen3 4B NexusPrime is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3 4B NexusPrime by ZeroXClem — VRAM 8.2GB, 40K context

Name: Qwen3 4B NexusPrime
Author: ZeroXClem

Qwen3 4B NexusPrime is an open-source language model by ZeroXClem. Features: 4b LLM, VRAM: 8.2GB, Context: 40K, License: apache-2.0, Code Generating, Merged, LLM Explorer Score: 0.18.

Merged Model Base model:prithivmlmods/boote... Base model:prithivmlmods/canum... Base model:prithivmlmods/cetus... Base model:prithivmlmods/segue... Base model:prithivmlmods/turei... Codegen Conversational En Endpoints compatible Qwen3 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/ZeroXClem/Qwen3-4B-NexusPrime

Qwen3 4B NexusPrime Parameters and Internals

LLM Name	Qwen3 4B NexusPrime
Repository 🤗	https://huggingface.co/ZeroXClem/Qwen3-4B-NexusPrime
Base Model(s)	Cetus Qwen3 4B GeneralThought Tureis Qwen3 QWQ 4B Exp Canum Qwen3 R1 4B ICoT Bootes Qwen3 Coder Reasoning Segue Qwen3 DeepScaleR Preview prithivMLmods/Cetus-Qwen3_4B-GeneralThought prithivMLmods/Tureis-Qwen3_QWQ-4B-Exp prithivMLmods/Canum-Qwen3_R1-4B-iCoT prithivMLmods/Bootes-Qwen3_Coder-Reasoning prithivMLmods/Segue-Qwen3_DeepScaleR-Preview
Merged Model	Yes
Model Size	4b
Required VRAM	8.2 GB
Updated	2026-08-03
Maintainer	ZeroXClem
Model Type	qwen3
Model Files	1.0 GB: 1-of-9 1.0 GB: 2-of-9 1.0 GB: 3-of-9 1.0 GB: 4-of-9 1.0 GB: 5-of-9 1.0 GB: 6-of-9 1.0 GB: 7-of-9 1.0 GB: 8-of-9 0.2 GB: 9-of-9
Supported Languages	en
Generates Code	Yes
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	40960
Model Max Length	40960
Transformers Version	4.52.0.dev0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
Vocabulary Size	151669
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen3 4B NexusPrime 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 Qwen3 4B NexusPrime

Best Alternatives	Context / RAM	Downloads	Likes
Mini Coder 4B	256K / 8.1 GB	53	4
FluentlyQwen3 Coder 4B 0909	40K / 8 GB	18	8
FluentlyQwen3 Coder 4B	40K / 8 GB	8	0
...tzar Coder F1 6B Brainstorm20x	40K / 11.9 GB	206	9
...DER Instruct 12B Brainstorm20x	40K / 47.3 GB	41	3
...ODER Instruct 6B Brainstorm20x	40K / 11.9 GB	10	0
Blitzar Coder 4B F.1	40K / 8.1 GB	13	9
Bootes Qwen3 Coder Reasoning	40K / 8.1 GB	21	9
Mini Coder 4B OptiQ 4bit	256K / 3 GB	310	1

Note: green Score (e.g. "73.2") means that the model is better than ZeroXClem/Qwen3-4B-NexusPrime.