What are the hardware requirements for Zephyr Quiklang 3B GPTQ?

Zephyr Quiklang 3B GPTQ requires approximately 1.8 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 Zephyr Quiklang 3B GPTQ and how large is it?

Zephyr Quiklang 3B GPTQ is developed by TheBloke, a model with 3b 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 Zephyr Quiklang 3B GPTQ?

Zephyr Quiklang 3B GPTQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Zephyr Quiklang 3B GPTQ by TheBloke — VRAM 1.8GB, 4K context

Name: Zephyr Quiklang 3B GPTQ
Author: TheBloke

Zephyr Quiklang 3B GPTQ is an open-source language model by TheBloke. Features: 3b LLM, VRAM: 1.8GB, Context: 4K, License: mit, Quantized, LLM Explorer Score: 0.1.

4-bit Causal lm Conversational Custom code Dataset:teknium/openhermes Dataset:unalignment/toxic-dpo-... Feature-extraction Gptq Quantized Region:us Safetensors Stablelm epoch

Model Card on HF 🤗: https://huggingface.co/TheBloke/zephyr-quiklang-3b-GPTQ

Zephyr Quiklang 3B GPTQ Parameters and Internals

Model Type

stablelm_epoch

Additional Notes

This is a finetune of StableLM-Zephyr-3B with two datasets (openhermes and toxic-dpo).

Training Details

Data Sources:

unalignment/toxic-dpo-v0.1, teknium/openhermes

Data Volume:

10000 samples

Context Length:

1024

Hardware Used:

1xA6000-48GB

Input Output

Input Format:

<|system|> {system_message}~~ <|user|> {prompt}~~ <|assistant|>

LLM Name	Zephyr Quiklang 3B GPTQ
Repository 🤗	https://huggingface.co/TheBloke/zephyr-quiklang-3b-GPTQ
Model Name	Zephyr Quiklang 3B
Model Creator	wbag
Base Model(s)	Zephyr Quiklang 3B Walmart-the-bag/zephyr-quiklang-3b
Model Size	3b
Required VRAM	1.8 GB
Updated	2026-07-25
Maintainer	TheBloke
Model Type	stablelm_epoch
Model Files	1.8 GB
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	StableLMEpochForCausalLM
License	mit
Context Length	4096
Model Max Length	4096
Transformers Version	4.37.0.dev0
Tokenizer Class	GPTNeoXTokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	50304
Torch Data Type	float16

Rank the Zephyr Quiklang 3B 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 Zephyr Quiklang 3B GPTQ

Best Alternatives	Context / RAM	Downloads	Likes
Stable Code 3B GPTQ	16K / 1.8 GB	10	12
Zephyr Quiklang 3B 4K GPTQ	4K / 1.8 GB	2	2
Dopeystableplats 3B V1 GPTQ	4K / 1.8 GB	6	0
Stablelm Zephyr 3B GPTQ	4K / 1.8 GB	10	12
...ling Stable Lm 3B 4e1t V0 GPTQ	4K / 1.8 GB	4	1
Rocket 3B GPTQ	4K / 1.8 GB	8	0
Nous Capybara 3B V1.9 GPTQ	4K / 1.8 GB	8	8
Akins 3B GPTQ	4K / 1.8 GB	6	2
Marx 3B V3 GPTQ	4K / 1.8 GB	5	2
Stable Code 3B Mlx	16K / 5.6 GB	17	1

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/zephyr-quiklang-3b-GPTQ.