What are the hardware requirements for Miqu 1 70B Sf GPTQ?

Miqu 1 70B Sf GPTQ requires approximately 40.7 GB of VRAM and supports a context window of 31K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Miqu 1 70B Sf GPTQ and how large is it?

Miqu 1 70B Sf GPTQ is developed by LoneStriker, a model with 70b 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 Miqu 1 70B Sf GPTQ?

Miqu 1 70B Sf GPTQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Miqu 1 70B Sf GPTQ by LoneStriker — VRAM 40.7GB, 31K context

Name: Miqu 1 70B Sf GPTQ
Author: LoneStriker

Miqu 1 70B Sf GPTQ is an open-source language model by LoneStriker. Features: 70b LLM, VRAM: 40.7GB, Context: 31K, License: mit, Quantized, LLM Explorer Score: 0.11.

4bit Conversational Endpoints compatible Gptq Llama Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/LoneStriker/miqu-1-70b-sf-GPTQ

Miqu 1 70B Sf GPTQ Parameters and Internals

Model Type

text generation

Additional Notes

Dequantised from q5 to f16 and transposed to PyTorch; implemented with usage example.

Input Output

Input Format:

text input with specific prompt structure

Accepted Modalities:

text

Output Format:

text

Performance Tips:

Many GPUs are recommended for use.

LLM Name	Miqu 1 70B Sf GPTQ
Repository 🤗	https://huggingface.co/LoneStriker/miqu-1-70b-sf-GPTQ
Model Size	70b
Required VRAM	40.7 GB
Updated	2026-07-04
Maintainer	LoneStriker
Model Type	llama
Model Files	40.7 GB
GPTQ Quantization	Yes
Quantization Type	gptq\|4bit
Model Architecture	LlamaForCausalLM
License	mit
Context Length	32764
Model Max Length	32764
Transformers Version	4.37.1
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float16

Rank the Miqu 1 70B Sf GPTQ 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

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...B Instruct AutoRound GPTQ 4bit	128K / 39.9 GB	517	6
...B Instruct AutoRound GPTQ 4bit	128K / 39.9 GB	129	0
...ama 3.1 70B Instruct Gptq 4bit	128K / 39.9 GB	7	4
Opus V1.2 70B Marlin	32K / 36.4 GB	8	0
MoMo 70B Lora 1.8.4 DPO GPTQ	32K / 41.3 GB	5	1
MoMo 70B Lora 1.8.6 DPO GPTQ	32K / 41.3 GB	4	1
Tess 70B V1.6 Marlin	31K / 36.3 GB	7	1
Midnight Miqu 70B V1.5 GPTQ32G	31K / 40.7 GB	43	4
...Midnight Miqu 70B V1.0 GPTQ32G	31K / 40.7 GB	8	2
Senku 70B GPTQ 4bit	31K / 36.7 GB	6	1

Note: green Score (e.g. "73.2") means that the model is better than LoneStriker/miqu-1-70b-sf-GPTQ.