What are the hardware requirements for Deepseek Coder 5.7bmqa Base?

Deepseek Coder 5.7bmqa Base requires approximately 11.4 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 5.7bmqa Base and how large is it?

Deepseek Coder 5.7bmqa Base is developed by deepseek-ai. 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 5.7bmqa Base?

Deepseek Coder 5.7bmqa Base is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Deepseek Coder 5.7bmqa Base by deepseek-ai — VRAM 11.4GB, 16K context

Name: Deepseek Coder 5.7bmqa Base
Author: deepseek-ai

Deepseek Coder 5.7bmqa Base is an open-source language model by deepseek-ai. Features: LLM, VRAM: 11.4GB, Context: 16K, License: other, Code Generating, LLM Explorer Score: 0.1.

Codegen Deploy:azure Endpoints compatible Llama Pytorch Region:us Sharded

Model Card on HF 🤗: https://huggingface.co/deepseek-ai/deepseek-coder-5.7bmqa-base

Deepseek Coder 5.7bmqa Base Parameters and Internals

LLM Name	Deepseek Coder 5.7bmqa Base
Repository 🤗	https://huggingface.co/deepseek-ai/deepseek-coder-5.7bmqa-base
Required VRAM	11.4 GB
Updated	2026-08-06
Maintainer	deepseek-ai
Model Type	llama
Model Files	9.9 GB: 1-of-2 1.5 GB: 2-of-2
Generates Code	Yes
Model Architecture	LlamaForCausalLM
License	other
Context Length	16384
Model Max Length	16384
Transformers Version	4.33.1
Tokenizer Class	LlamaTokenizerFast
Beginning of Sentence Token	<｜begin▁of▁sentence｜>
End of Sentence Token	<｜end▁of▁sentence｜>
Vocabulary Size	32256
Torch Data Type	bfloat16

Rank the Deepseek Coder 5.7bmqa Base 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

Quantized Models of the Deepseek Coder 5.7bmqa Base

Model	Likes	Downloads	VRAM
...epseek Coder 5.7bmqa Base GGUF	5	1982	2 GB
...eepseek Coder 5.7bmqa Base AWQ	0	13	3 GB

Best Alternatives to Deepseek Coder 5.7bmqa Base

Best Alternatives	Context / RAM	Downloads	Likes
Codellama Cairo Instruct GGUF	16K / 4.1 GB	32	1
Tinyllama Coder Py V15	4K / 0.7 GB	98	0
Tinyllama Coder Py V16	4K / 0.7 GB	12	0
CodeGen Instruct	16K / 0.8 GB	130	0

Note: green Score (e.g. "73.2") means that the model is better than deepseek-ai/deepseek-coder-5.7bmqa-base.