What are the hardware requirements for DeepSeek Coder V2 Lite Base AWQ?

DeepSeek Coder V2 Lite Base AWQ requires approximately 9.1 GB of VRAM and supports a context window of 160K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed DeepSeek Coder V2 Lite Base AWQ and how large is it?

DeepSeek Coder V2 Lite Base AWQ is developed by TechxGenus, a model with 15.7b 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 DeepSeek Coder V2 Lite Base AWQ?

DeepSeek Coder V2 Lite 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 V2 Lite Base AWQ by TechxGenus — VRAM 9.1GB, 160K context

Name: DeepSeek Coder V2 Lite Base AWQ
Author: TechxGenus

DeepSeek Coder V2 Lite Base AWQ is an open-source language model by TechxGenus. Features: 15.7b LLM, VRAM: 9.1GB, Context: 160K, License: other, Quantized, Code Generating, LLM Explorer Score: 0.13.

Arxiv:2401.06066 4-bit Awq Codegen Conversational Custom code Deepseek v2 Endpoints compatible Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/TechxGenus/DeepSeek-Coder-V2-Lite-Base-AWQ

DeepSeek Coder V2 Lite Base AWQ Parameters and Internals

Model Type

Code language model, Mixture-of-Experts (MoE)

Supported Languages

total (; languages_proficiency:{)

Training Details

Data Sources:

Multi-source high-quality corpus

Data Volume:

6 trillion tokens

Methodology:

Mixture-of-Experts (MoE) approach

Context Length:

128000

Hardware Used:

80GB*8 GPUs

Input Output

Input Format:

Text input for code completion, chat completion.

Accepted Modalities:

text

Output Format:

Generated code or chat responses.

LLM Name	DeepSeek Coder V2 Lite Base AWQ
Repository 🤗	https://huggingface.co/TechxGenus/DeepSeek-Coder-V2-Lite-Base-AWQ
Model Size	15.7b
Required VRAM	9.1 GB
Updated	2026-08-05
Maintainer	TechxGenus
Model Type	deepseek_v2
Model Files	5.0 GB: 1-of-2 4.1 GB: 2-of-2
AWQ Quantization	Yes
Quantization Type	awq
Generates Code	Yes
Model Architecture	DeepseekV2ForCausalLM
License	other
Context Length	163840
Model Max Length	163840
Transformers Version	4.41.2
Tokenizer Class	LlamaTokenizer
Padding Token	<｜end▁of▁sentence｜>
Vocabulary Size	102400
Torch Data Type	float16

Rank the DeepSeek Coder V2 Lite 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 V2 Lite Base AWQ

Best Alternatives	Context / RAM	Downloads	Likes
...eek Coder V2 Lite Instruct AWQ	160K / 9.1 GB	7853	11
...eepSeek Coder V2 Lite Instruct	160K / 31.4 GB	542062	628
Dsv2 Lite Coder Codeio Pp	160K / 31.4 GB	2	2
DeepSeek Coder V2 Lite Base	160K / 31.4 GB	5350	114
...2 Lite Instruct FlashAttnPatch	160K / 31.4 GB	24	0

Note: green Score (e.g. "73.2") means that the model is better than TechxGenus/DeepSeek-Coder-V2-Lite-Base-AWQ.