What are the hardware requirements for Llama 33B Instructed?

Llama 33B Instructed requires approximately 65.2 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama 33B Instructed and how large is it?

Llama 33B Instructed is developed by Secbone, a model with 33b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Llama 33B Instructed perform on standard benchmarks?

Llama 33B Instructed has the following published scores: MMLU 60.5. Compare against reference models on this page or on the LLM Explorer leaderboards.

Llama 33B Instructed by Secbone — VRAM 65.2GB, 2K context

Name: Llama 33B Instructed
Author: Secbone

Llama 33B Instructed is an open-source language model by Secbone. Features: 33b LLM, VRAM: 65.2GB, Context: 2K, License: gpl-3.0, Quantized, LLM Explorer Score: 0.12, Arc: 64.6, HellaSwag: 86.2, MMLU: 60.5, GSM8K: 14.4.

Endpoints compatible F16 Fp16 Ggml Gguf Llama Pytorch Q5 Q5 1 Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Secbone/llama-33B-instructed

Llama 33B Instructed Parameters and Internals

Model Type

text generation, instruction-following

LLM Name	Llama 33B Instructed
Repository 🤗	https://huggingface.co/Secbone/llama-33B-instructed
Model Size	33b
Required VRAM	65.2 GB
Updated	2026-07-27
Maintainer	Secbone
Model Type	llama
Model Files	5.4 GB 5.4 GB 5.4 GB 5.4 GB 5.4 GB 5.4 GB 5.4 GB 5.4 GB 5.4 GB 5.4 GB 5.4 GB 5.4 GB 0.6 GB 5.4 GB 5.4 GB 5.4 GB 5.4 GB 2.9 GB 5.4 GB 5.4 GB 5.4 GB 5.4 GB 5.4 GB 5.4 GB 2.4 GB 9.8 GB: 1-of-7 10.0 GB: 2-of-7 9.9 GB: 3-of-7 9.9 GB: 4-of-7 9.9 GB: 5-of-7 10.0 GB: 6-of-7 5.7 GB: 7-of-7 9.8 GB: 1-of-7 10.0 GB: 2-of-7 9.9 GB: 3-of-7 9.9 GB: 4-of-7 9.9 GB: 5-of-7 10.0 GB: 6-of-7 5.7 GB: 7-of-7
GGML Quantization	Yes
GGUF Quantization	Yes
Quantization Type	fp16\|ggml\|q5\|q5_1\|gguf\|f16\|q8_0
Model Architecture	LlamaForCausalLM
License	gpl-3.0
Context Length	2048
Model Max Length	2048
Transformers Version	4.33.2
Tokenizer Class	LlamaTokenizer
Beginning of Sentence Token	<s>
End of Sentence Token	</s>
Unk Token	<unk>
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Llama 33B Instructed 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 Llama 33B Instructed

Best Alternatives	Context / RAM	Downloads	Likes
Vicuna 33B V1.3 GGUF	2K / 34.6 GB	11	0
Guanaco 33B 4bit	2K / 16.9 GB	5	10
...Interpreter DS 33B Hf 4bit Mlx	16K / 19.1 GB	270	7
...erpreter DS 33B 4.0bpw H6 EXL2	16K / 17.1 GB	8	4
...rpreter DS 33B 4.65bpw H6 EXL2	16K / 19.8 GB	5	3
...erpreter DS 33B 5.0bpw H6 EXL2	16K / 21.2 GB	6	1
...erpreter DS 33B 6.0bpw H6 EXL2	16K / 25.3 GB	8	0
...erpreter DS 33B 8.0bpw H8 EXL2	16K / 33.5 GB	5	1
...e DeepSeek 33B 4.65bpw H6 EXL2	16K / 19.8 GB	7	2
...se DeepSeek 33B 4.0bpw H6 EXL2	16K / 17.1 GB	5	2

Note: green Score (e.g. "73.2") means that the model is better than Secbone/llama-33B-instructed.