What are the hardware requirements for Apricot Wildflower 20?

Apricot Wildflower 20 requires approximately 14.4 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 and how large is it?

Apricot Wildflower 20 is developed by crumb, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Apricot Wildflower 20 perform on standard benchmarks?

Apricot Wildflower 20 has the following published scores: MMLU 63.38. Compare against reference models on this page or on the LLM Explorer leaderboards.

Apricot Wildflower 20 by crumb — VRAM 14.4GB, 32K context

Name: Apricot Wildflower 20
Author: crumb

Apricot Wildflower 20 is an open-source language model by crumb. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.12, Arc: 59.6, HellaSwag: 81.8, MMLU: 63.4, GSM8K: 34.

Endpoints compatible Mistral Model-index Region:us Safetensors Sharded Tensorflow

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

Apricot Wildflower 20 Parameters and Internals

Model Type

text generation

Additional Notes

emphasized the casual nature of the project's inception.

Training Details

Data Sources:

Openwebtext2 with a >=20 reddit score filter

Methodology:

Finetuned for 1k steps with a combined lm loss and distillation loss using training logits from Mixtral.

Input Output

Accepted Modalities:

text

Output Format:

text

LLM Name	Apricot Wildflower 20
Repository 🤗	https://huggingface.co/crumb/apricot-wildflower-20
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-08-04
Maintainer	crumb
Model Type	mistral
Model Files	4.9 GB: 1-of-3 5.0 GB: 2-of-3 4.5 GB: 3-of-3
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.36.0.dev0
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Apricot Wildflower 20 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

Quantized Models of the Apricot Wildflower 20

Model	Likes	Downloads	VRAM
Apricot Wildflower 20 GGUF	3	343	3 GB
Apricot Wildflower 20 GPTQ	1	12	4 GB
Apricot Wildflower 20 AWQ	1	3	4 GB

Best Alternatives to Apricot Wildflower 20

Best Alternatives	Context / RAM	Downloads	Likes
...Nemo Instruct 2407 Abliterated	1000K / 24.5 GB	220	20
MegaBeam Mistral 7B 512K	512K / 14.4 GB	8470	54
SpydazWeb AI HumanAI RP	512K / 14.4 GB	16	1
SpydazWeb AI HumanAI 002	512K / 14.4 GB	18	1
...daz Web AI ChatML 512K Project	512K / 14.5 GB	12	0
MegaBeam Mistral 7B 300K	282K / 14.4 GB	3779	16
MegaBeam Mistral 7B 300K	282K / 14.4 GB	8018	17
Hebrew Mistral 7B 200K	256K / 30 GB	23	15
Astral 256K 7B	250K / 14.4 GB	9	0
Astral 256K 7B V2	250K / 14.4 GB	8	0

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