What are the hardware requirements for Deepseek Llm 67B Chat?

Deepseek Llm 67B Chat requires approximately 135 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 Llm 67B Chat and how large is it?

Deepseek Llm 67B Chat is developed by deepseek-ai, a model with 67b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Deepseek Llm 67B Chat perform on standard benchmarks?

Deepseek Llm 67B Chat has the following published scores: MMLU 62.8, LMSYS ELO 1184. Compare against reference models on this page or on the LLM Explorer leaderboards.

Deepseek Llm 67B Chat by deepseek-ai — VRAM 135GB, 4K context

Name: Deepseek Llm 67B Chat
Author: deepseek-ai

Deepseek Llm 67B Chat is an open-source language model by deepseek-ai. Features: 67b LLM, VRAM: 135GB, Context: 4K, License: other, LLM Explorer Score: 0.33, ELO: 1184, Arc: 90.1, HellaSwag: 82, MMLU: 62.8, GSM8K: 77.

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

Model Card on HF 🤗: https://huggingface.co/deepseek-ai/deepseek-llm-67b-chat

Deepseek Llm 67B Chat Benchmarks

LMSys ELO: 1184 vs 1272 (so35)^-6.9%

ARC: 90.1 vs 96.7 (so35)^-6.8%

HellaSwag: 82 vs 95.3 (gpt4)^-14%

MMLU: 62.8 vs 88.3 (so35)^-28.9%

GSM8K: 77 vs 96.4 (so35)^-20.1%

OpenCompas: 57.8 vs 73.3 (gpt4)^-21.1%

Exam: 70.7 vs 77.2 (gpt4)^-8.4%

Language: 37.6 vs 62 (gpt4)^-39.4%

Knowledge: 52.6 vs 73.5 (gpt4)^-28.4%

Understand: 58.7 vs 70 (gpt4)^-16.1%

Reasoning: 61 vs 74.4 (gpt4)^-18%

LLME Score: 0.33498

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Deepseek Llm 67B Chat (deepseek-ai/deepseek-llm-67b-chat)

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Deepseek Llm 67B Chat Parameters and Internals

Model Type

text generation

Additional Notes

The model is open-source, comes with an MIT License for code, and is subject to a separate model license.

Supported Languages

English (fluent), Chinese (fluent)

Training Details

Data Volume:

2 trillion tokens

Methodology:

scratch with fine-tuning

Input Output

Input Format:

structured as chat messages

Accepted Modalities:

text

Output Format:

text

Performance Tips:

Avoid using system prompts as they are not compatible with the model version.

LLM Name	Deepseek Llm 67B Chat
Repository 🤗	https://huggingface.co/deepseek-ai/deepseek-llm-67b-chat
Model Size	67b
Required VRAM	135 GB
Updated	2026-05-08
Maintainer	deepseek-ai
Model Type	llama
Model Files	10.0 GB: 1-of-14 10.0 GB: 2-of-14 9.7 GB: 3-of-14 9.7 GB: 4-of-14 9.7 GB: 5-of-14 9.7 GB: 6-of-14 9.7 GB: 7-of-14 9.7 GB: 8-of-14 9.7 GB: 9-of-14 9.7 GB: 10-of-14 9.7 GB: 11-of-14 9.7 GB: 12-of-14 9.7 GB: 13-of-14 8.3 GB: 14-of-14
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

Quantized Models of the Deepseek Llm 67B Chat

Model	Likes	Downloads	VRAM
Deepseek Llm 67B Chat GGUF	43	3064	28 GB
Deepseek Llm 67B Chat AWQ	5	30	37 GB
Deepseek Llm 67B Chat GPTQ	8	13	36 GB

Best Alternatives to Deepseek Llm 67B Chat

Best Alternatives	Context / RAM	Downloads	Likes
Deepseek Llm 67B Base	4K / 135 GB	20663	128
...penbuddy Deepseek 67B V18.1 4K	4K / 135 GB	8182	1
Openbuddy Deepseek 67B V15.2	4K / 135 GB	1905	10
...penbuddy Deepseek 67B V15.3 4K	4K / 135 GB	6	1
Openbuddy Deepseek 67B V15.1	4K / 135 GB	562	1
...penbuddy Deepseek 67B V15 Base	4K / 135 GB	126	0
...penbuddy Deepseek 67B V15.3 4K	4K / 135 GB	5	1
Deepmoney 67B Chat	4K / 135 GB	18	23
DeepSeek 67B MMIQC	4K / 135 GB	9	1
...67B Spicy 3.1 1 5.0bpw H6 EXL2	4K / 43.7 GB	4	1

Rank the Deepseek Llm 67B Chat Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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Release v20260328a

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