What are the hardware requirements for Vigogne 2 13B Instruct?

Vigogne 2 13B Instruct requires approximately 25.9 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 Vigogne 2 13B Instruct and how large is it?

Vigogne 2 13B Instruct is developed by bofenghuang, a model with 13b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Vigogne 2 13B Instruct perform on standard benchmarks?

Vigogne 2 13B Instruct has the following published scores: MMLU 55.92. Compare against reference models on this page or on the LLM Explorer leaderboards.

Vigogne 2 13B Instruct by bofenghuang — VRAM 25.9GB, 4K context

Name: Vigogne 2 13B Instruct
Author: bofenghuang

Vigogne 2 13B Instruct is an open-source language model by bofenghuang. Features: 13b LLM, VRAM: 25.9GB, Context: 4K, Instruction-Based, LLM Explorer Score: 0.1, Arc: 61.2, HellaSwag: 83.3, MMLU: 55.9, GSM8K: 2.1.

Fr Instruct Llama Llama2 Pytorch Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/bofenghuang/vigogne-2-13b-instruct

Vigogne 2 13B Instruct Parameters and Internals

Model Type

text generation, instruction-following

Use Cases

Areas:

research, applications utilizing French instructions

Limitations:

model might generate harmful or biased content, incorrect information or unhelpful answers

Additional Notes

The model is designed for instruction-following in the French language.

Supported Languages

fr (native)

LLM Name	Vigogne 2 13B Instruct
Repository 🤗	https://huggingface.co/bofenghuang/vigogne-2-13b-instruct
Model Size	13b
Required VRAM	25.9 GB
Updated	2026-07-27
Maintainer	bofenghuang
Model Type	llama
Instruction-Based	Yes
Model Files	1.9 GB: 1-of-14 1.9 GB: 2-of-14 1.9 GB: 3-of-14 1.9 GB: 4-of-14 1.9 GB: 5-of-14 1.9 GB: 6-of-14 1.9 GB: 7-of-14 1.9 GB: 8-of-14 1.9 GB: 9-of-14 1.9 GB: 10-of-14 1.9 GB: 11-of-14 1.9 GB: 12-of-14 1.9 GB: 13-of-14 1.2 GB: 14-of-14 1.9 GB: 1-of-14 1.9 GB: 2-of-14 1.9 GB: 3-of-14 1.9 GB: 4-of-14 1.9 GB: 5-of-14 1.9 GB: 6-of-14 1.9 GB: 7-of-14 1.9 GB: 8-of-14 1.9 GB: 9-of-14 1.9 GB: 10-of-14 1.9 GB: 11-of-14 1.9 GB: 12-of-14 1.9 GB: 13-of-14 1.2 GB: 14-of-14
Supported Languages	fr
Model Architecture	LlamaForCausalLM
Context Length	4096
Model Max Length	4096
Transformers Version	4.32.0.dev0
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 Vigogne 2 13B Instruct 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

Quantized Models of the Vigogne 2 13B Instruct

Model	Likes	Downloads	VRAM
Vigogne 2 13B Instruct GGUF	3	992	5 GB
Vigogne 2 13B Instruct GGML	6	5	5 GB
Vigogne 2 13B Instruct GPTQ	3	11	7 GB

Best Alternatives to Vigogne 2 13B Instruct

Best Alternatives	Context / RAM	Downloads	Likes
NexusRaven V2 13B	16K / 26 GB	105	472
CodeLlama 13B Instruct Hf	16K / 26 GB	2469	160
CodeLlama 13B MORepair	16K / 26 GB	9	2
CodeLlama 13B Instruct Hf	16K / 26 GB	369	29
TableLLM 13B	16K / 26 GB	98	34
NexusRaven 13B	16K / 26 GB	37	106
Panda Coder 13B	16K / 26 GB	11	14
... Llama 2 13B Instruct Text2sql	16K / 26 GB	8	28
Gen Sim	16K / 0.3 GB	4	3
Llama 3 13B Instruct Ft	8K / 26.1 GB	10	2

Note: green Score (e.g. "73.2") means that the model is better than bofenghuang/vigogne-2-13b-instruct.