What are the hardware requirements for SuperDeepseek V4 Flash Abliterated MQ 2xDGX?

SuperDeepseek V4 Flash Abliterated MQ 2xDGX requires approximately 145.1 GB of VRAM and supports a context window of 1024K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed SuperDeepseek V4 Flash Abliterated MQ 2xDGX and how large is it?

SuperDeepseek V4 Flash Abliterated MQ 2xDGX is developed by Jiunsong, a model with 1m 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 SuperDeepseek V4 Flash Abliterated MQ 2xDGX?

SuperDeepseek V4 Flash Abliterated MQ 2xDGX is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

SuperDeepseek V4 Flash Abliterated MQ 2xDGX by Jiunsong — VRAM 145.1GB, 1024K context

Name: SuperDeepseek V4 Flash Abliterated MQ 2xDGX
Author: Jiunsong

SuperDeepseek V4 Flash Abliterated MQ 2xDGX is an open-source language model by Jiunsong. Features: 1m LLM, VRAM: 145.1GB, Context: 1024K, License: mit, LLM Explorer Score: 0.4.

1m-context 8-bit Base model:deepseek-ai/deepsee... Base model:finetune:deepseek-a... Bf16 Deepseek-v4 Deepseek v4 Dgx-spark En Endpoints compatible Fp4 Fp8 Ko Long-context Mixed-precision Mixture-of-experts Obliteratus Quantized Reasoning Region:us Safetensors Sharded Supertune Tensorflow Tool-calling Uncensored Vllm

Model Card on HF 🤗: https://huggingface.co/Jiunsong/SuperDeepseek-V4-Flash-abliterated-MQ-2xDGX

SuperDeepseek V4 Flash Abliterated MQ 2xDGX Parameters and Internals

LLM Name	SuperDeepseek V4 Flash Abliterated MQ 2xDGX
Repository 🤗	https://huggingface.co/Jiunsong/SuperDeepseek-V4-Flash-abliterated-MQ-2xDGX
Base Model(s)	DeepSeek V4 Flash 0731 deepseek-ai/DeepSeek-V4-Flash-0731
Model Size	1m
Required VRAM	145.1 GB
Updated	2026-08-13
Maintainer	Jiunsong
Model Type	deepseek_v4
Model Files	1.1 GB: 1-of-48 3.6 GB: 2-of-48 3.6 GB: 3-of-48 3.6 GB: 4-of-48 3.6 GB: 5-of-48 3.6 GB: 6-of-48 3.6 GB: 7-of-48 3.6 GB: 8-of-48 3.6 GB: 9-of-48 3.6 GB: 10-of-48 3.6 GB: 11-of-48 3.6 GB: 12-of-48 3.6 GB: 13-of-48 3.6 GB: 14-of-48 3.6 GB: 15-of-48 3.6 GB: 16-of-48 3.6 GB: 17-of-48 3.6 GB: 18-of-48 3.6 GB: 19-of-48 3.6 GB: 20-of-48 3.6 GB: 21-of-48 3.6 GB: 22-of-48 3.6 GB: 23-of-48 3.6 GB: 24-of-48 3.6 GB: 25-of-48 3.6 GB: 26-of-48 3.6 GB: 27-of-48 3.6 GB: 28-of-48 3.6 GB: 29-of-48 3.6 GB: 30-of-48 3.6 GB: 31-of-48 3.6 GB: 32-of-48 3.6 GB: 33-of-48 3.6 GB: 34-of-48 3.6 GB: 35-of-48 3.6 GB: 36-of-48 3.6 GB: 37-of-48 3.6 GB: 38-of-48 3.6 GB: 39-of-48 3.6 GB: 40-of-48 3.6 GB: 41-of-48
Supported Languages	en ko
Model Architecture	DeepseekV4ForCausalLM
License	mit
Context Length	1048576
Model Max Length	1048576
Transformers Version	4.57.1
Vocabulary Size	129280
Torch Data Type	bfloat16

Rank the SuperDeepseek V4 Flash Abliterated MQ 2xDGX 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 SuperDeepseek V4 Flash Abliterated MQ 2xDGX

Best Alternatives	Context / RAM	Downloads	Likes
...rDeepseek V4 Flash Abliterated	1024K / 145.1 GB	38	3