What are the hardware requirements for Apricot Wildflower 20 GGUF?

Apricot Wildflower 20 GGUF requires approximately 3.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Apricot Wildflower 20 GGUF and how large is it?

Apricot Wildflower 20 GGUF is developed by TheBloke. 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 GGUF?

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

Apricot Wildflower 20 GGUF by TheBloke — VRAM 3.1GB

Name: Apricot Wildflower 20 GGUF
Author: TheBloke

Apricot Wildflower 20 GGUF is an open-source language model by TheBloke. Features: LLM, VRAM: 3.1GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.11.

Base model:crumb/apricot-wildf... Base model:quantized:crumb/apr... Gguf Mistral Quantized Region:us

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

Apricot Wildflower 20 GGUF Parameters and Internals

Model Type

mistral

Additional Notes

The quantized versions of the model in GGUF format were provided by TheBloke using hardware from Massed Compute. GGUF supports various UIs and libraries and is compatible with versions of llama.cpp from August 27, 2023 onwards.

Training Details

Data Sources:

Openwebtext2

Methodology:

Fine-tuned for 1k steps with a combined lm loss and distillation loss on Openwebtext2 with a >=20 reddit score filter with training logits from Mixtral.

Input Output

Input Format:

{prompt}

LLM Name	Apricot Wildflower 20 GGUF
Repository 🤗	https://huggingface.co/TheBloke/apricot-wildflower-20-GGUF
Model Name	Apricot Wildflower 20
Model Creator	Maxine
Base Model(s)	Apricot Wildflower 20 crumb/apricot-wildflower-20
Required VRAM	3.1 GB
Updated	2026-07-29
Maintainer	TheBloke
Model Type	mistral
Model Files	3.1 GB 3.8 GB 3.5 GB 3.2 GB 4.1 GB 4.4 GB 4.1 GB 5.0 GB 5.1 GB 5.0 GB 5.9 GB 7.7 GB
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	AutoModel
License	apache-2.0

Rank the Apricot Wildflower 20 GGUF 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 GGUF

Best Alternatives	Context / RAM	Downloads	Likes
ComicBot V.2 Gguf	32K / 5 GB	54	0
Qwen3 Medical GRPO GGUF	0K / 1.7 GB	440	6
Gemma2 WizardLM	0K / 5.2 GB	22	0
...ixtral 8x7B Instruct V0.1 GGUF	0K / 15.6 GB	18491	655
Marco O1 GGUF	0K / 3 GB	262	6
Phi 2 GGUF	0K / 1.2 GB	21217	233
Dolphin 2.5 Mixtral 8x7b GGUF	0K / 15.6 GB	18101	314
Dolphin 2.7 Mixtral 8x7b GGUF	0K / 15.6 GB	12812	176
GOAT Llama3.1 V0.1	0K / 0.2 GB	39	3
Mixtral 8x7B V0.1 GGUF	0K / 15.6 GB	4192	438

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