What are the hardware requirements for Deepseek Coder 1.3B Base AWQ?

Deepseek Coder 1.3B Base AWQ requires approximately 0.9 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 Deepseek Coder 1.3B Base AWQ and how large is it?

Deepseek Coder 1.3B Base AWQ is developed by TheBloke, a model with 1.3b 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 Deepseek Coder 1.3B Base AWQ?

Deepseek Coder 1.3B Base AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Deepseek Coder 1.3B Base AWQ by TheBloke — VRAM 0.9GB, 16K context

Name: Deepseek Coder 1.3B Base AWQ
Author: TheBloke

Deepseek Coder 1.3B Base AWQ is an open-source language model by TheBloke. Features: 1.3b LLM, VRAM: 0.9GB, Context: 16K, License: other, Quantized, Code Generating, LLM Explorer Score: 0.09.

4-bit Awq Base model:deepseek-ai/deepsee... Base model:quantized:deepseek-... Codegen Llama Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/TheBloke/deepseek-coder-1.3b-base-AWQ

Deepseek Coder 1.3B Base AWQ Parameters and Internals

Model Type

deepseek

Use Cases

Areas:

Research, Commercial applications

Primary Use Cases:

Code completion, Code insertion, Project-level code understanding

Limitations:

Limited to code and related linguistic input processing

Considerations:

Ensure usage aligns with the code model's focus on programming tasks.

Additional Notes

Part of a series of code language models starting from 1B to 33B versions. Model size of 1.3B for this variant.

Supported Languages

English (fluent), Chinese (fluent)

Training Details

Data Sources:

2T tokens including 87% code and 13% linguistic data

Data Volume:

2T tokens

Methodology:

Pre-trained with a window size of 16K and fill-in-the-blank task for code completion.

Context Length:

16384

Model Architecture:

Multi-Head Attention

Input Output

Input Format:

{prompt}

Accepted Modalities:

text

Output Format:

Generated code or text completion

LLM Name	Deepseek Coder 1.3B Base AWQ
Repository 🤗	https://huggingface.co/TheBloke/deepseek-coder-1.3b-base-AWQ
Model Name	Deepseek Coder 1.3B Base
Model Creator	DeepSeek
Base Model(s)	deepseek-ai/deepseek-coder-1.3b-base deepseek-ai/deepseek-coder-1.3b-base
Model Size	1.3b
Required VRAM	0.9 GB
Updated	2026-08-07
Maintainer	TheBloke
Model Type	deepseek
Model Files	0.9 GB
AWQ Quantization	Yes
Quantization Type	awq
Generates Code	Yes
Model Architecture	LlamaForCausalLM
License	other
Context Length	16384
Model Max Length	16384
Transformers Version	4.35.0
Tokenizer Class	LlamaTokenizerFast
Beginning of Sentence Token	<｜begin▁of▁sentence｜>
End of Sentence Token	<｜end▁of▁sentence｜>
Vocabulary Size	32256
Torch Data Type	float16

Rank the Deepseek Coder 1.3B Base 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 Deepseek Coder 1.3B Base AWQ

Best Alternatives	Context / RAM	Downloads	Likes
...epseek Coder 1.3B Instruct AWQ	8K / 0.9 GB	80	5
Imagine V8	16K / 2.7 GB	702	1
Deepseek Coder 1.3B Instruct	16K / 2.7 GB	92255	176
Llm4decompile 1.3B V2	16K / 2.7 GB	1272	11
...1.3B Chat And Function Calling	16K / 2.7 GB	238	0
Speechless Coder Ds 1.3B	16K / 2.7 GB	180	0
Deepseek Coder 1.3B Chat	16K / 2.7 GB	98	1
...c Deepseek Coder 1.3B Instruct	16K / 5.4 GB	5	0
CursorCore DS 1.3B SR	16K / 2.7 GB	29	2
CursorCore DS 1.3B LC	16K / 2.7 GB	27	0

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/deepseek-coder-1.3b-base-AWQ.