What are the hardware requirements for Falcon 7B Instruct GPTQ?

Falcon 7B Instruct GPTQ requires approximately 5.9 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Falcon 7B Instruct GPTQ and how large is it?

Falcon 7B Instruct GPTQ is developed by TheBloke, 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 Falcon 7B Instruct GPTQ?

Falcon 7B Instruct GPTQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Falcon 7B Instruct GPTQ by TheBloke — VRAM 5.9GB

Name: Falcon 7B Instruct GPTQ
Author: TheBloke

Falcon 7B Instruct GPTQ is an open-source language model by TheBloke. Features: 7b LLM, VRAM: 5.9GB, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.07.

Arxiv:1911.02150 Arxiv:2005.14165 Arxiv:2104.09864 Arxiv:2205.14135 4-bit Custom code Dataset:tiiuae/falcon-refinedw... En Gptq Instruct Quantized Refinedwebmodel Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/TheBloke/Falcon-7B-Instruct-GPTQ

Falcon 7B Instruct GPTQ Parameters and Internals

Model Type

Causal decoder-only

Use Cases

Areas:

Research, Personal Use

Primary Use Cases:

Chatbots, Instruction-following applications

Limitations:

Not optimized for NLP benchmarks, Carries web stereotypes and biases

Considerations:

Develop guardrails and take precautions for production use.

Supported Languages

en (English), fr (French)

Training Details

Data Sources:

tiiuae/falcon-refinedweb, Bai ze, GPT4All, GPTeacher

Data Volume:

250M tokens

Methodology:

Fined-tuned on instruct/chat datasets

Context Length:

2048

Hardware Used:

32 A100 40GB GPUs in P4d instances

Model Architecture:

Positionnal embeddings: rotary; Attention: multiquery and FlashAttention; Decoder-block: parallel attention/MLP with a single layer norm

Responsible Ai Considerations

Fairness:

Model mainly trained on English data; may carry stereotypes and biases from the web.

Mitigation Strategies:

Develop guardrails and precautions for production use.

Input Output

Input Format:

Prompt: 'User: prompt'

Accepted Modalities:

Text

Output Format:

Text completion

Performance Tips:

AutoGPTQ for better performance

LLM Name	Falcon 7B Instruct GPTQ
Repository 🤗	https://huggingface.co/TheBloke/Falcon-7B-Instruct-GPTQ
Base Model(s)	...on 7B Instruct Finance Advisor themanas021/falcon-7b-instruct-Finance_Advisor
Model Size	7b
Required VRAM	5.9 GB
Updated	2026-07-08
Maintainer	TheBloke
Model Type	RefinedWebModel
Instruction-Based	Yes
Model Files	5.9 GB
Supported Languages	en
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	RWForCausalLM
License	apache-2.0
Model Max Length	2048
Transformers Version	4.29.2
Is Biased	0
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	65024
Torch Data Type	float32

Rank the Falcon 7B Instruct GPTQ 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 Falcon 7B Instruct GPTQ

Best Alternatives	Context / RAM	Downloads	Likes
Falcon 7B Instruct GPTQ	0K / 5.9 GB	20	4
Falcon 7B Instruct Autogptq	0K / 4.8 GB	8	1
Falcon 7B Instruct 8bit	0K / 7.2 GB	5	0
Ct2 Int8 Falcon 7B Instruct	0K / GB	5	0
Falcon 7b Python Instructions	0K / 13.8 GB	5	1
Docsgpt 7B Falcon	0K / 13.8 GB	85	15
Falcon 7B Instruct V2	0K / 28.9 GB	5	1
... Falcon 7B Instruct W4 G64 AWQ	0K / 4.2 GB	18	5
Falcon 7B Finance	0K / 13.8 GB	18	3
Vigogne Falcon 7B Instruct	0K / 14.4 GB	10	1

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Falcon-7B-Instruct-GPTQ.