What are the hardware requirements for AmberChat GPTQ?

AmberChat GPTQ 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 AmberChat GPTQ and how large is it?

AmberChat GPTQ 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 AmberChat GPTQ?

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

AmberChat GPTQ by TheBloke — VRAM 3.9GB, 2K context

Name: AmberChat GPTQ
Author: TheBloke

AmberChat GPTQ is an open-source language model by TheBloke. Features: 6.7b LLM, VRAM: 3.9GB, Context: 2K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.1.

4-bit Base model:llm360/amberchat Base model:quantized:llm360/am... Dataset:icybee/share gpt 90k v... Dataset:wizardlm/wizardlm evol... En Gptq Instruct Llama Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/TheBloke/AmberChat-GPTQ

AmberChat GPTQ Parameters and Internals

Model Type

Language model with the same architecture as LLaMA-7B

Additional Notes

Model includes quantization options provided by TheBloke.

Supported Languages

English (NLP)

Training Details

Data Sources:

WizardLM/WizardLM_evol_instruct_V2_196k, icybee/share_gpt_90k_v1

Data Volume:

Total: 233k rows

Context Length:

2048

Input Output

Input Format:

A chat prompt with format: 'USER: {prompt} ASSISTANT: '

Accepted Modalities:

text

Output Format:

text generation

LLM Name	AmberChat GPTQ
Repository 🤗	https://huggingface.co/TheBloke/AmberChat-GPTQ
Model Name	AmberChat
Model Creator	LLM360
Base Model(s)	AmberChat LLM360/AmberChat
Model Size	6.7b
Required VRAM	3.9 GB
Updated	2026-07-30
Maintainer	TheBloke
Model Type	amber
Instruction-Based	Yes
Model Files	3.9 GB
Supported Languages	en
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	2048
Model Max Length	2048
Transformers Version	4.36.0.dev0
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
Vocabulary Size	32000
Torch Data Type	float16

Rank the AmberChat 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 AmberChat GPTQ

Best Alternatives	Context / RAM	Downloads	Likes
...pseek Coder 6.7B Instruct GPTQ	16K / 3.9 GB	514	25
Magicoder S DS 6.7B GPTQ	16K / 3.9 GB	7	7
Medicine Chat GPTQ	4K / 3.9 GB	20	6
Law Chat GPTQ	4K / 3.9 GB	5	4
Finance Chat GPTQ	4K / 3.9 GB	4	3
...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
...rpreter DS 6.7B 6.0bpw H6 EXL2	16K / 5.2 GB	5	2
...rpreter DS 6.7B 8.0bpw H8 EXL2	16K / 6.9 GB	3	2
...rpreter DS 6.7B 4.0bpw H6 EXL2	16K / 3.6 GB	1	1

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