What are the hardware requirements for Deepseek Math 7B Base?

Deepseek Math 7B Base requires approximately 13.9 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 Deepseek Math 7B Base and how large is it?

Deepseek Math 7B Base is developed by deepseek-ai, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Deepseek Math 7B Base perform on standard benchmarks?

Deepseek Math 7B Base has the following published scores: MMLU 57.25. Compare against reference models on this page or on the LLM Explorer leaderboards.

Deepseek Math 7B Base by deepseek-ai — VRAM 13.9GB, 4K context

Name: Deepseek Math 7B Base
Author: deepseek-ai

Deepseek Math 7B Base is an open-source language model by deepseek-ai. Features: 7b LLM, VRAM: 13.9GB, Context: 4K, License: other, LLM Explorer Score: 0.18, Arc: 52.2, HellaSwag: 69.5, MMLU: 57.3, GSM8K: 59.2.

Arxiv:2402.03300 Deploy:azure Endpoints compatible Llama Pytorch Region:us Sharded

Model Card on HF 🤗: https://huggingface.co/deepseek-ai/deepseek-math-7b-base

Deepseek Math 7B Base Parameters and Internals

Model Type

text generation, multimodal

LLM Name	Deepseek Math 7B Base
Repository 🤗	https://huggingface.co/deepseek-ai/deepseek-math-7b-base
Model Size	7b
Required VRAM	13.9 GB
Updated	2026-07-27
Maintainer	deepseek-ai
Model Type	llama
Model Files	10.0 GB: 1-of-2 3.9 GB: 2-of-2
Model Architecture	LlamaForCausalLM
License	other
Context Length	4096
Model Max Length	4096
Transformers Version	4.33.1
Tokenizer Class	LlamaTokenizerFast
Beginning of Sentence Token	<｜begin▁of▁sentence｜>
End of Sentence Token	<｜end▁of▁sentence｜>
Vocabulary Size	102400
Torch Data Type	bfloat16

Rank the Deepseek Math 7B 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

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Note: green Score (e.g. "73.2") means that the model is better than deepseek-ai/deepseek-math-7b-base.