What are the hardware requirements for Finance LLM AWQ?

Finance LLM AWQ requires approximately 3.9 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 Finance LLM AWQ and how large is it?

Finance LLM AWQ is developed by TheBloke, a model with 6.7b 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 Finance LLM AWQ?

Finance LLM AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Finance LLM AWQ by TheBloke — VRAM 3.9GB, 2K context

Name: Finance LLM AWQ
Author: TheBloke

Finance LLM AWQ is an open-source language model by TheBloke. Features: 6.7b LLM, VRAM: 3.9GB, Context: 2K, License: other, Quantized, Instruction-Based, LLM Explorer Score: 0.1.

Arxiv:2309.09530 4-bit Awq Base model:adaptllm/finance-ll... Base model:quantized:adaptllm/... Dataset:gair/lima Dataset:open-orca/openorca Dataset:wizardlm/wizardlm evol... En Finance Instruct Llama Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/TheBloke/finance-LLM-AWQ

Finance LLM AWQ Parameters and Internals

Model Type

llama

Additional Notes

AWQ is an efficient low-bit weight quantization method supporting 4-bit quantization, offering faster Transformers-based inference with comparable or better quality.

Supported Languages

en (full-proficiency)

Training Details

Data Sources:

Open-Orca/OpenOrca, GAIR/lima, WizardLM/WizardLM_evol_instruct_V2_196k

Methodology:

continued pre-training on domain-specific corpora and transforming large-scale pre-training corpora into reading comprehension texts

Context Length:

2048

Hardware Used:

Massed Compute

Input Output

Input Format:

[INST] <> {system_message} <> {prompt} [/INST]

Accepted Modalities:

text

LLM Name	Finance LLM AWQ
Repository 🤗	https://huggingface.co/TheBloke/finance-LLM-AWQ
Model Name	Finance LLM
Model Creator	AdaptLLM
Base Model(s)	Finance LLM AdaptLLM/finance-LLM
Model Size	6.7b
Required VRAM	3.9 GB
Updated	2026-05-30
Maintainer	TheBloke
Model Type	llama
Instruction-Based	Yes
Model Files	3.9 GB
Supported Languages	en
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	LlamaForCausalLM
License	other
Context Length	2048
Model Max Length	2048
Transformers Version	4.36.2
Tokenizer Class	LlamaTokenizer
Padding Token	<pad>
Vocabulary Size	32001
Torch Data Type	float16

Rank the Finance LLM AWQ 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 Finance LLM AWQ

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...epseek Coder 6.7B Instruct AWQ	16K / 3.9 GB	291702	19
Magicoder S DS 6.7B AWQ	16K / 3.9 GB	8	9
Law Chat AWQ	4K / 3.9 GB	7	4
Finance Chat AWQ	4K / 3.9 GB	7	3
Medicine Chat AWQ	4K / 3.9 GB	3	3
AdaptLLM Finance Chat AWQ	4K / 3.9 GB	0	1
Medicine LLM AWQ	2K / 3.9 GB	6	4
AmberChat AWQ	2K / 3.9 GB	4	1
...LI LlumiX 32K Instruct F16 0.2	32K / 13.5 GB	8	1
...LI LlumiX 32K Instruct F16 0.1	32K / 13.5 GB	10	0

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/finance-LLM-AWQ.