What are the hardware requirements for Trinity 13B 6.0bpw H6 EXL2?

Trinity 13B 6.0bpw H6 EXL2 requires approximately 10 GB of VRAM and supports a context window of 16K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Trinity 13B 6.0bpw H6 EXL2 and how large is it?

Trinity 13B 6.0bpw H6 EXL2 is developed by LoneStriker, a model with 13b 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 Trinity 13B 6.0bpw H6 EXL2?

Trinity 13B 6.0bpw H6 EXL2 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Trinity 13B 6.0bpw H6 EXL2 by LoneStriker — VRAM 10GB, 16K context

Name: Trinity 13B 6.0bpw H6 EXL2
Author: LoneStriker

Trinity 13B 6.0bpw H6 EXL2 is an open-source language model by LoneStriker. Features: 13b LLM, VRAM: 10GB, Context: 16K, License: llama2, Quantized, Code Generating, LLM Explorer Score: 0.1.

Codegen Custom code Endpoints compatible Exl2 Fp16 Llama Pytorch Quantized Region:us Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/LoneStriker/Trinity-13B-6.0bpw-h6-exl2

Trinity 13B 6.0bpw H6 EXL2 Parameters and Internals

Model Type

autonomous agents, text generation

Use Cases

Areas:

research, commercial applications

Applications:

autonomous agent creation

LLM Name	Trinity 13B 6.0bpw H6 EXL2
Repository 🤗	https://huggingface.co/LoneStriker/Trinity-13B-6.0bpw-h6-exl2
Model Size	13b
Required VRAM	10 GB
Updated	2026-07-16
Maintainer	LoneStriker
Model Type	llama
Model Files	8.6 GB: 1-of-2 1.4 GB: 2-of-2
Quantization Type	fp16\|exl2
Generates Code	Yes
Model Architecture	LlamaForCausalLM
License	llama2
Context Length	16384
Model Max Length	16384
Transformers Version	4.36.2
Tokenizer Class	CodeLlamaTokenizer
Padding Token	</s>
Vocabulary Size	32016
Torch Data Type	bfloat16

Rank the Trinity 13B 6.0bpw H6 EXL2 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 Trinity 13B 6.0bpw H6 EXL2

Best Alternatives	Context / RAM	Downloads	Likes
WhiteRabbitNeo 13B V1	16K / 26 GB	3146	453
CodeLlama 13B Python Fp16	16K / 26 GB	121	25
CodeLlama 13B Fp16	16K / 26 GB	9	67
CodeLlama 13B Instruct Fp16	16K / 26 GB	137	28
Codellama 13B Bnb 4bit	16K / 7.2 GB	129	5
...Llama 13B Instruct Hf 4bit MLX	16K / 7.8 GB	113	3
Trinity 13B	16K / 26 GB	14	15
Trinity 13B 5.0bpw H6 EXL2	16K / 8.4 GB	7	1
Trinity 13B 3.0bpw H6 EXL2	16K / 5.2 GB	3	1
Trinity 13B 4.0bpw H6 EXL2	16K / 6.8 GB	0	1

Note: green Score (e.g. "73.2") means that the model is better than LoneStriker/Trinity-13B-6.0bpw-h6-exl2.