What are the hardware requirements for Dendrite 22Bchk2 F16?

Dendrite 22Bchk2 F16 requires approximately 43.7 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Dendrite 22Bchk2 F16 and how large is it?

Dendrite 22Bchk2 F16 is developed by Envoid, 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 Dendrite 22Bchk2 F16?

Dendrite 22Bchk2 F16 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Dendrite 22Bchk2 F16 by Envoid — VRAM 43.7GB, 4K context

Name: Dendrite 22Bchk2 F16
Author: Envoid

Dendrite 22Bchk2 F16 is an open-source language model by Envoid. Features: 22b LLM, VRAM: 43.7GB, Context: 4K, Quantized, LLM Explorer Score: 0.08.

Endpoints compatible Fp16 Llama Pytorch Quantized Region:us Sharded

Model Card on HF 🤗: https://huggingface.co/Envoid/Dendrite-22Bchk2-F16

Dendrite 22Bchk2 F16 Parameters and Internals

Model Type

text processing, language model

Additional Notes

This is an FP-16 version of a checkpoint, suitable for further training or merging.

Training Details

Data Sources:

hand-selected raw text

Data Volume:

20MB

Methodology:

LoRA (Low-Rank Adaptation)

Training Time:

10 hours

LLM Name	Dendrite 22Bchk2 F16
Repository 🤗	https://huggingface.co/Envoid/Dendrite-22Bchk2-F16
Model Size	22b
Required VRAM	43.7 GB
Updated	2026-08-01
Maintainer	Envoid
Model Type	llama
Model Files	9.8 GB: 1-of-5 10.0 GB: 2-of-5 9.9 GB: 3-of-5 9.9 GB: 4-of-5 4.1 GB: 5-of-5
Quantization Type	fp16
Model Architecture	LlamaForCausalLM
Context Length	4096
Model Max Length	4096
Transformers Version	4.31.0
Tokenizer Class	LlamaTokenizer
Beginning of Sentence Token	<s>
End of Sentence Token	</s>
Unk Token	<unk>
Vocabulary Size	32000
Torch Data Type	float16

Rank the Dendrite 22Bchk2 F16 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

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Note: green Score (e.g. "73.2") means that the model is better than Envoid/Dendrite-22Bchk2-F16.