What are the hardware requirements for Apricot Wildflower 20 AWQ?

Apricot Wildflower 20 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 Apricot Wildflower 20 AWQ and how large is it?

Apricot Wildflower 20 AWQ is developed by TheBloke, 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 Apricot Wildflower 20 AWQ?

Apricot Wildflower 20 AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Apricot Wildflower 20 AWQ by TheBloke — VRAM 4.2GB, 32K context

Name: Apricot Wildflower 20 AWQ
Author: TheBloke

Apricot Wildflower 20 AWQ is an open-source language model by TheBloke. Features: 7.2b LLM, VRAM: 4.2GB, Context: 32K, License: apache-2.0, Quantized, LLM Explorer Score: 0.1.

4-bit Awq Base model:crumb/apricot-wildf... Base model:quantized:crumb/apr... Mistral Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/TheBloke/apricot-wildflower-20-AWQ

Apricot Wildflower 20 AWQ Parameters and Internals

Model Type

mistral, low-bit quantization

Additional Notes

AWQ models supported on Linux and Windows with NVidia GPUs only. macOS users advised to use GGUF models.

Training Details

Data Sources:

Openwebtext2, Mixtral training logits

Methodology:

Finetuned for 1k steps using a combined LM loss and distillation loss, with a >=20 Reddit score filter.

Model Architecture:

Mistral-7b

LLM Name	Apricot Wildflower 20 AWQ
Repository 🤗	https://huggingface.co/TheBloke/apricot-wildflower-20-AWQ
Model Name	Apricot Wildflower 20
Model Creator	Maxine
Base Model(s)	Apricot Wildflower 20 crumb/apricot-wildflower-20
Model Size	7.2b
Required VRAM	4.2 GB
Updated	2026-07-13
Maintainer	TheBloke
Model Type	mistral
Model Files	4.2 GB
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.36.2
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32000
Torch Data Type	float16

Rank the Apricot Wildflower 20 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 Apricot Wildflower 20 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
Hc Mistral Alpaca Merged AWQ	32K / 4.2 GB	5	0
Garrulus AWQ	32K / 4.2 GB	7	2
HamSter 0.1 AWQ	32K / 4.2 GB	5	2

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/apricot-wildflower-20-AWQ.