What are the hardware requirements for Acolyte 22B?

Acolyte 22B requires approximately 44.7 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Acolyte 22B and how large is it?

Acolyte 22B is developed by rAIfle, a model with 22b 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 Acolyte 22B?

Acolyte 22B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Acolyte 22B by rAIfle — VRAM 44.7GB, 128K context

Name: Acolyte 22B
Author: rAIfle

Acolyte 22B is an open-source language model by rAIfle. Features: 22b LLM, VRAM: 44.7GB, Context: 128K, Instruction-Based, Merged, LLM Explorer Score: 0.14.

Merged Model Base model:raifle/acolyte-lora Base model:unsloth/mistral-sma... Conversational Deploy:azure Endpoints compatible Instruct Lora Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/rAIfle/Acolyte-22B

Acolyte 22B Parameters and Internals

Additional Notes

Decent enough for its size.

Training Details

Data Sources:

random datasets on top of Mistral-Small-Instruct-2409

Methodology:

LoRA and SLERP at 0.5

LLM Name	Acolyte 22B
Repository 🤗	https://huggingface.co/rAIfle/Acolyte-22B
Base Model(s)	Mistral Small Instruct 2409 Mistral Small Instruct 2409 rAIfle/Acolyte-LORA unsloth/Mistral-Small-Instruct-2409 unsloth/Mistral-Small-Instruct-2409 rAIfle/Acolyte-LORA
Merged Model	Yes
Model Size	22b
Required VRAM	44.7 GB
Updated	2026-07-13
Maintainer	rAIfle
Model Type	mistral
Instruction-Based	Yes
Model Files	4.9 GB: 1-of-10 4.9 GB: 2-of-10 5.0 GB: 3-of-10 5.0 GB: 4-of-10 4.9 GB: 5-of-10 5.0 GB: 6-of-10 5.0 GB: 7-of-10 4.9 GB: 8-of-10 5.0 GB: 9-of-10 0.1 GB: 10-of-10
Model Architecture	MistralForCausalLM
Context Length	131072
Model Max Length	131072
Transformers Version	4.44.2
Tokenizer Class	LlamaTokenizer
Padding Token	[control_748]
Vocabulary Size	32768
LoRA Model	Yes
Torch Data Type	bfloat16

Rank the Acolyte 22B 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 Acolyte 22B

Best Alternatives	Context / RAM	Downloads	Likes
MS Schisandra 22B V0.2	128K / 44.7 GB	8	9
...ntheon RP Pure 1.6.2 22B Small	128K / 44.7 GB	17	35
MS Meadowlark 22B	128K / 44.7 GB	13	16
MS Inky 2409 22B	128K / 44.7 GB	5	0
MS Springydragon 2409 22B	128K / 44.7 GB	8	0
MS Moingooistral 2409 22B	128K / 44.7 GB	7	0
MS Quadrosiac 2409 22B	128K / 44.7 GB	6	0
... V4x1.6.2RP Cydonia VXXX 22B 8	128K / 44.7 GB	5	5
MS Fujin 2409 22B	128K / 44.7 GB	5	0
MS Dampf 2409 22B	128K / 44.7 GB	5	0

Note: green Score (e.g. "73.2") means that the model is better than rAIfle/Acolyte-22B.