What are the hardware requirements for BurningBruce 003 EXL2 B8.0?

BurningBruce 003 EXL2 B8.0 requires approximately 24.3 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 BurningBruce 003 EXL2 B8.0 and how large is it?

BurningBruce 003 EXL2 B8.0 is developed by h2m, a model with 7b 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 BurningBruce 003 EXL2 B8.0?

BurningBruce 003 EXL2 B8.0 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

BurningBruce 003 EXL2 B8.0 by h2m — VRAM 24.3GB, 32K context

Name: BurningBruce 003 EXL2 B8.0
Author: h2m

BurningBruce 003 EXL2 B8.0 is an open-source language model by h2m. Features: 7b LLM, VRAM: 24.3GB, Context: 32K, License: apache-2.0, Quantized, LLM Explorer Score: 0.11.

Arxiv:2101.03961 Conversational En Endpoints compatible Exl2 Merge Mixtral Moe Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/h2m/BurningBruce-003-exl2-b8.0

BurningBruce 003 EXL2 B8.0 Parameters and Internals

Model Type

Mixture of Experts (MoE)

Use Cases

Areas:

research, development

Additional Notes

This model is a Mixture of Experts (MoE) made with mergekit.

Supported Languages

en (English)

Input Output

Accepted Modalities:

text

LLM Name	BurningBruce 003 EXL2 B8.0
Repository 🤗	https://huggingface.co/h2m/BurningBruce-003-exl2-b8.0
Model Size	7b
Required VRAM	24.3 GB
Updated	2026-07-26
Maintainer	h2m
Model Type	mixtral
Model Files	8.6 GB: 1-of-3 8.5 GB: 2-of-3 7.2 GB: 3-of-3
Supported Languages	en
Quantization Type	exl2
Model Architecture	MixtralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.36.2
Tokenizer Class	LlamaTokenizer
Padding Token	<s>
Vocabulary Size	32000
Torch Data Type	float16

Rank the BurningBruce 003 EXL2 B8.0 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 BurningBruce 003 EXL2 B8.0

Best Alternatives	Context / RAM	Downloads	Likes
...izardLM 2 4x7B MoE EXL2 3 0bpw	32K / 9.4 GB	2	1
Buttercup 4x7B 6bpw EXL2	32K / 18.4 GB	6	2
...ixtral 2x7b DPO 8.0bpw H8 EXL2	32K / 13 GB	4	4
...ixtral 2x7b DPO 6.0bpw H6 EXL2	32K / 9.8 GB	6	1
...ixtral 2x7b DPO 4.0bpw H6 EXL2	32K / 6.7 GB	2	1
...ixtral 2x7b DPO 5.0bpw H6 EXL2	32K / 8.3 GB	1	1
...t V0.2 2x7B MoE 6.0bpw H6 EXL2	32K / 9.9 GB	3	1
...iveFusion 4x7b MoE EXL2 3.5BPW	8K / 10.8 GB	8	1
...lue Orchid 2x7b 8.0bpw H8 EXL2	8K / 13 GB	7	5
...lue Orchid 2x7b 5.0bpw H6 EXL2	8K / 8.2 GB	8	4

Note: green Score (e.g. "73.2") means that the model is better than h2m/BurningBruce-003-exl2-b8.0.