What are the hardware requirements for Qwen3 Coder Next NVFP4 GB10?

Qwen3 Coder Next NVFP4 GB10 requires approximately 45.8 GB of VRAM and supports a context window of 256K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3 Coder Next NVFP4 GB10 and how large is it?

Qwen3 Coder Next NVFP4 GB10 is developed by ucbye. 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 Coder Next NVFP4 GB10?

Qwen3 Coder Next NVFP4 GB10 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3 Coder Next NVFP4 GB10 by ucbye — VRAM 45.8GB, 256K context

Name: Qwen3 Coder Next NVFP4 GB10
Author: ucbye

Qwen3 Coder Next NVFP4 GB10 is an open-source language model by ucbye. Features: LLM, VRAM: 45.8GB, Context: 256K, License: apache-2.0, Code Generating, LLM Explorer Score: 0.35.

4-bit Base model:quantized:saricles/... Base model:saricles/qwen3-code... Codegen Coding Compressed-tensors Conversational Dgx-spark En Endpoints compatible Gb10 Mirror Moe Nvfp4 Quantized Qwen3 Qwen3 next Region:us Safetensors Sharded Tensorflow Vllm

Model Card on HF 🤗: https://huggingface.co/ucbye/Qwen3-Coder-Next-NVFP4-GB10

Qwen3 Coder Next NVFP4 GB10 Parameters and Internals

LLM Name	Qwen3 Coder Next NVFP4 GB10
Repository 🤗	https://huggingface.co/ucbye/Qwen3-Coder-Next-NVFP4-GB10
Base Model(s)	saricles/Qwen3-Coder-Next-NVFP4-GB10 saricles/Qwen3-Coder-Next-NVFP4-GB10
Required VRAM	45.8 GB
Updated	2026-09-04
Maintainer	ucbye
Model Type	qwen3_next
Model Files	5.0 GB: 1-of-10 5.0 GB: 2-of-10 5.0 GB: 3-of-10 5.0 GB: 4-of-10 5.0 GB: 5-of-10 5.0 GB: 6-of-10 5.0 GB: 7-of-10 5.0 GB: 8-of-10 5.0 GB: 9-of-10 0.8 GB: 10-of-10
Supported Languages	en
Generates Code	Yes
Model Architecture	Qwen3NextForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Transformers Version	4.57.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Errors	replace

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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