What are the hardware requirements for Hc Mistral Alpaca Merged AWQ?

Hc Mistral Alpaca Merged AWQ requires approximately 4.2 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Hc Mistral Alpaca Merged AWQ and how large is it?

Hc Mistral Alpaca Merged AWQ is developed by parlance-labs, a model with 7.2b 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 Hc Mistral Alpaca Merged AWQ?

Hc Mistral Alpaca Merged AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Hc Mistral Alpaca Merged AWQ by parlance-labs — VRAM 4.2GB, 32K context

Name: Hc Mistral Alpaca Merged AWQ
Author: parlance-labs

Hc Mistral Alpaca Merged AWQ is an open-source language model by parlance-labs. Features: 7.2b LLM, VRAM: 4.2GB, Context: 32K, Quantized, Merged, LLM Explorer Score: 0.11.

Merged Model 4-bit Awq Endpoints compatible Mistral Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/parlance-labs/hc-mistral-alpaca-merged-awq

Hc Mistral Alpaca Merged AWQ Parameters and Internals

Model Type

Causal Language Model

Additional Notes

The model is quantized using AWQ with 4-bit precision, optimized for lower memory usage and faster inference, while maintaining competitive performance.

Input Output

Input Format:

Text inputs for causal language modeling.

Accepted Modalities:

text

Output Format:

Text output generated by the model.

LLM Name	Hc Mistral Alpaca Merged AWQ
Repository 🤗	https://huggingface.co/parlance-labs/hc-mistral-alpaca-merged-awq
Merged Model	Yes
Model Size	7.2b
Required VRAM	4.2 GB
Updated	2026-08-02
Maintainer	parlance-labs
Model Type	mistral
Model Files	4.2 GB
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	MistralForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.38.2
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32000
Torch Data Type	float16

Rank the Hc Mistral Alpaca Merged AWQ 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 Hc Mistral Alpaca Merged AWQ

Best Alternatives	Context / RAM	Downloads	Likes
Feedback Wizard 4bit AWQ	32K / 4.2 GB	6	0
Ryze AWQ 4bit	32K / 4.2 GB	5	0
...V3 Plot Chat Roleplay Chat AWQ	32K / 4.2 GB	7	0
...lot Engine Step Json Short AWQ	32K / 4.2 GB	5	0
MistralLite AWQ	32K / 4.2 GB	27	6
LemonadeRP 4.5.3 AWQ	32K / 4.2 GB	5	0
Functionary Small V2.4 AWQ	32K / 4.2 GB	1	1
Garrulus AWQ	32K / 4.2 GB	7	2
HamSter 0.1 AWQ	32K / 4.2 GB	5	2
Phoenix AWQ	32K / 4.2 GB	12	1

Note: green Score (e.g. "73.2") means that the model is better than parlance-labs/hc-mistral-alpaca-merged-awq.