What are the hardware requirements for SVD Qwen3 Coder Next Thinking?

SVD Qwen3 Coder Next Thinking requires approximately 318.7 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 SVD Qwen3 Coder Next Thinking and how large is it?

SVD Qwen3 Coder Next Thinking is developed by win10, a model with 79.7b 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 SVD Qwen3 Coder Next Thinking?

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

SVD Qwen3 Coder Next Thinking by win10 — VRAM 318.7GB, 256K context

Name: SVD Qwen3 Coder Next Thinking
Author: win10

SVD Qwen3 Coder Next Thinking is an open-source language model by win10. Features: 79.7b LLM, VRAM: 318.7GB, Context: 256K, Code Generating, Merged, LLM Explorer Score: 0.22.

Merged Model Codegen Endpoints compatible Qwen3 next Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/win10/SVD-Qwen3-Coder-Next-Thinking

SVD Qwen3 Coder Next Thinking Parameters and Internals

LLM Name	SVD Qwen3 Coder Next Thinking
Repository 🤗	https://huggingface.co/win10/SVD-Qwen3-Coder-Next-Thinking
Merged Model	Yes
Model Size	79.7b
Required VRAM	318.7 GB
Updated	2026-08-11
Maintainer	win10
Model Type	qwen3_next
Model Files	10.0 GB: 1-of-32 10.0 GB: 2-of-32 10.0 GB: 3-of-32 10.0 GB: 4-of-32 10.0 GB: 5-of-32 10.0 GB: 6-of-32 10.0 GB: 7-of-32 10.0 GB: 8-of-32 10.0 GB: 9-of-32 10.0 GB: 10-of-32 10.0 GB: 11-of-32 10.0 GB: 12-of-32 10.0 GB: 13-of-32 10.0 GB: 14-of-32 10.0 GB: 15-of-32 10.0 GB: 16-of-32 10.0 GB: 17-of-32 10.0 GB: 18-of-32 10.0 GB: 19-of-32 10.0 GB: 20-of-32 10.0 GB: 21-of-32 10.0 GB: 22-of-32 10.0 GB: 23-of-32 10.0 GB: 24-of-32 10.0 GB: 25-of-32 10.0 GB: 26-of-32 10.0 GB: 27-of-32 10.0 GB: 28-of-32 10.0 GB: 29-of-32 10.0 GB: 30-of-32 10.0 GB: 31-of-32 8.7 GB: 32-of-32
Generates Code	Yes
Model Architecture	Qwen3NextForCausalLM
Context Length	262144
Model Max Length	262144
Transformers Version	4.57.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Errors	replace

Rank the SVD Qwen3 Coder Next Thinking capabilities

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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

Best Alternatives to SVD Qwen3 Coder Next Thinking

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3 Coder Next	256K / 159.4 GB	908245	1546
Qwen3 Coder Next FP8	256K / 80.3 GB	669389	148
Qwen3 Coder Next FP8 Dynamic	256K / 83.4 GB	17864	45
Qwen3 Coder Next Base	256K / 159.4 GB	1910	70
Qwen3 Coder Next Bf16	256K / 159.7 GB	2193	3
Qwen3 Coder Next FP8	256K / 80.3 GB	1697	11
Qwen3 Coder Next Mxfp8	256K / 82.3 GB	254	1
Qwen3 Coder Next Mxfp4	256K / 42 GB	241	1
Qwen3 Coder Next	256K / 159.4 GB	976	27
Qwen3 Coder Next Base	256K / 159.4 GB	22	7

Note: green Score (e.g. "73.2") means that the model is better than win10/SVD-Qwen3-Coder-Next-Thinking.