What are the hardware requirements for Apricot Wildflower 20 GPTQ?

Apricot Wildflower 20 GPTQ 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 GPTQ and how large is it?

Apricot Wildflower 20 GPTQ 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 GPTQ?

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

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

Name: Apricot Wildflower 20 GPTQ
Author: TheBloke

Apricot Wildflower 20 GPTQ 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 Base model:crumb/apricot-wildf... Base model:quantized:crumb/apr... Gptq Mistral Quantized Region:us Safetensors

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

Apricot Wildflower 20 GPTQ Parameters and Internals

Model Type

Causal Language Model

Use Cases

Applications:

Text generation

Additional Notes

Quantised using hardware by Massed Compute with multiple parameter variations for different environments.

Training Details

Data Sources:

Openwebtext2, Mixtral

Methodology:

Finetuned for 1k steps with a combined lm loss and distillation loss. Filter applied on Openwebtext2 with a >=20 reddit score from Mixtral.

Hardware Used:

Provided by Massed Compute

Model Architecture:

Mistral-based architecture

LLM Name	Apricot Wildflower 20 GPTQ
Repository 🤗	https://huggingface.co/TheBloke/apricot-wildflower-20-GPTQ
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	2026-08-02
Maintainer	TheBloke
Model Type	mistral
Model Files	4.2 GB
GPTQ Quantization	Yes
Quantization Type	gptq
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	bfloat16

Rank the Apricot Wildflower 20 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

Best Alternatives to Apricot Wildflower 20 GPTQ

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Multi Verse Model GPTQ	32K / 4.2 GB	111	1
Garrulus GPTQ	32K / 4.2 GB	28	3
HamSter 0.1 GPTQ	32K / 4.2 GB	7	2
Phoenix GPTQ	32K / 4.2 GB	12	1
Mistral Ft Optimized 1227 GPTQ	32K / 4.2 GB	19	2
...hat 3.5 1210 Seraph Slerp GPTQ	32K / 4.2 GB	10	2
...h Openchat 3.5 1210 Slerp GPTQ	32K / 4.2 GB	6	1
Metis 0.5 GPTQ	32K / 4.2 GB	6	1
XDAN L1 Chat RL V1 GPTQ	32K / 4.2 GB	15	3
SAM GPTQ	32K / 4.2 GB	19	0

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