What are the hardware requirements for Ryze AWQ 4bit?

Ryze AWQ 4bit 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 Ryze AWQ 4bit and how large is it?

Ryze AWQ 4bit is developed by Fulcrum-AI, 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 Ryze AWQ 4bit?

Ryze AWQ 4bit is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Ryze AWQ 4bit by Fulcrum-AI — VRAM 4.2GB, 32K context

Name: Ryze AWQ 4bit
Author: Fulcrum-AI

Ryze AWQ 4bit is an open-source language model by Fulcrum-AI. Features: 7.2b LLM, VRAM: 4.2GB, Context: 32K, Quantized, LLM Explorer Score: 0.13.

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

Model Card on HF 🤗: https://huggingface.co/Fulcrum-AI/Ryze-AWQ-4bit

Ryze AWQ 4bit Parameters and Internals

LLM Name	Ryze AWQ 4bit
Repository 🤗	https://huggingface.co/Fulcrum-AI/Ryze-AWQ-4bit
Model Size	7.2b
Required VRAM	4.2 GB
Updated	2026-06-08
Maintainer	Fulcrum-AI
Model Type	mistral
Model Files	4.2 GB
AWQ Quantization	Yes
Quantization Type	awq\|4bit
Model Architecture	MistralForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.41.2
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32002
Torch Data Type	float16

Rank the Ryze AWQ 4bit 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 Ryze AWQ 4bit

Best Alternatives	Context / RAM	Downloads	Likes
Feedback Wizard 4bit AWQ	32K / 4.2 GB	6	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	36	6
LemonadeRP 4.5.3 AWQ	32K / 4.2 GB	5	0
Functionary Small V2.4 AWQ	32K / 4.2 GB	1	1
Hc Mistral Alpaca Merged AWQ	32K / 4.2 GB	5	0
Garrulus AWQ	32K / 4.2 GB	7	2
Phoenix AWQ	32K / 4.2 GB	28	1
HamSter 0.1 AWQ	32K / 4.2 GB	5	2

Note: green Score (e.g. "73.2") means that the model is better than Fulcrum-AI/Ryze-AWQ-4bit.