What are the hardware requirements for Fox 1 1.6B?

Fox 1 1.6B requires approximately 3.3 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Fox 1 1.6B and how large is it?

Fox 1 1.6B is developed by tensoropera, a model with 1.6b 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 Fox 1 1.6B?

Fox 1 1.6B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Fox 1 1.6B by tensoropera — VRAM 3.3GB, 8K context

Name: Fox 1 1.6B
Author: tensoropera

Fox 1 1.6B is an open-source language model by tensoropera. Features: 1.6b LLM, VRAM: 3.3GB, Context: 8K, License: apache-2.0, LLM Explorer Score: 0.15.

Arxiv:2411.05281 Conversational Deploy:azure En Endpoints compatible Llama Model-index Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/tensoropera/Fox-1-1.6B

Fox 1 1.6B Parameters and Internals

Model Type

text-generation

Additional Notes

Fox-1 is a base pretrained model that requires further fine-tuning for most use cases.

Training Details

Data Sources:

text, code

Data Volume:

3 trillion tokens

Methodology:

3-stage data curriculum

Context Length:

8000

Hardware Used:

8 H100 GPUs

Model Architecture:

decoder-only transformer-based small language model (SLM)

LLM Name	Fox 1 1.6B
Repository 🤗	https://huggingface.co/tensoropera/Fox-1-1.6B
Model Size	1.6b
Required VRAM	3.3 GB
Updated	2026-07-19
Maintainer	tensoropera
Model Type	llama
Model Files	3.3 GB
Supported Languages	en
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	8192
Model Max Length	8192
Transformers Version	4.39.3
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	256000
Torch Data Type	bfloat16

Rank the Fox 1 1.6B capabilities

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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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