What are the hardware requirements for Magicoder S DS 6.7B AWQ?

Magicoder S DS 6.7B AWQ requires approximately 3.9 GB of VRAM and supports a context window of 16K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Magicoder S DS 6.7B AWQ and how large is it?

Magicoder S DS 6.7B 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 Magicoder S DS 6.7B AWQ?

Magicoder S DS 6.7B AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Magicoder S DS 6.7B AWQ by TheBloke — VRAM 3.9GB, 16K context

Name: Magicoder S DS 6.7B AWQ
Author: TheBloke

Magicoder S DS 6.7B AWQ is an open-source language model by TheBloke. Features: 6.7b LLM, VRAM: 3.9GB, Context: 16K, License: other, Quantized, Instruction-Based, LLM Explorer Score: 0.1.

Arxiv:2305.06161 Arxiv:2312.02120 4-bit Awq Base model:ise-uiuc/magicoder-... Base model:quantized:ise-uiuc/... Dataset:ise-uiuc/magicoder-evo... Dataset:ise-uiuc/magicoder-oss... Instruct Llama Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/TheBloke/Magicoder-S-DS-6.7B-AWQ

Magicoder S DS 6.7B AWQ Parameters and Internals

Model Type

deepseek, text-generation

Use Cases

Areas:

coding tasks

Limitations:

may not work well in non-coding tasks

Considerations:

Users should be aware of the risks, biases, and limitations of the model.

Additional Notes

Magicoder models are trained on synthetic data generated by OpenAI models.

Training Details

Data Sources:

Magicoder-OSS-Instruct-75K, Magicoder-Evol-Instruct-110K

Methodology:

OSS-Instruct

Context Length:

16384

Input Output

Input Format:

@@ Instruction {prompt} @@ Response

Accepted Modalities:

text

LLM Name	Magicoder S DS 6.7B AWQ
Repository 🤗	https://huggingface.co/TheBloke/Magicoder-S-DS-6.7B-AWQ
Model Name	Magicoder S DS 6.7B
Model Creator	Intellligent Software Engineering (iSE
Base Model(s)	ise-uiuc/Magicoder-S-DS-6.7B ise-uiuc/Magicoder-S-DS-6.7B
Model Size	6.7b
Required VRAM	3.9 GB
Updated	2026-08-08
Maintainer	TheBloke
Model Type	deepseek
Instruction-Based	Yes
Model Files	3.9 GB
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	LlamaForCausalLM
License	other
Context Length	16384
Model Max Length	16384
Transformers Version	4.35.2
Tokenizer Class	LlamaTokenizer
Padding Token	<｜end▁of▁sentence｜>
Vocabulary Size	32256
Torch Data Type	float16

Rank the Magicoder S DS 6.7B 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 Magicoder S DS 6.7B AWQ

Best Alternatives	Context / RAM	Downloads	Likes
...epseek Coder 6.7B Instruct AWQ	16K / 3.9 GB	291702	19
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
Finance LLM AWQ	2K / 3.9 GB	12	5
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/Magicoder-S-DS-6.7B-AWQ.