What are the hardware requirements for WestLake 7B V2?

WestLake 7B V2 requires approximately 14.4 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed WestLake 7B V2 and how large is it?

WestLake 7B V2 is developed by senseable, 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 WestLake 7B V2 perform on standard benchmarks?

WestLake 7B V2 has the following published scores: MMLU 64.71. Compare against reference models on this page or on the LLM Explorer leaderboards.

WestLake 7B V2 by senseable — VRAM 14.4GB, 32K context

Name: WestLake 7B V2
Author: senseable

WestLake 7B V2 is an open-source language model by senseable. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.16, Arc: 73, HellaSwag: 88.7, MMLU: 64.7, GSM8K: 67.6.

Deploy:azure En Endpoints compatible Mistral Model-index Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/senseable/WestLake-7B-v2

WestLake 7B V2 Parameters and Internals

Model Type

text-generation

Use Cases

Areas:

Creative Writing, Education, Gaming, Customer Support, Social Media

Additional Notes

Welcome to the documentation of Westlake-7B, a cutting-edge language model designed for exceptional role-play and text generation tasks. This README file aims to provide an overview of our capabilities, usage guidelines, and potential applications.

Release Notes

Version:

Notes:

Version 2 trained 1 additional epoch cycle for 3 total

LLM Name	WestLake 7B V2
Repository 🤗	https://huggingface.co/senseable/WestLake-7B-v2
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-08-07
Maintainer	senseable
Model Type	mistral
Model Files	4.9 GB: 1-of-3 5.0 GB: 2-of-3 4.5 GB: 3-of-3
Supported Languages	en
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.36.1
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
Vocabulary Size	32000
Torch Data Type	float16

Rank the WestLake 7B V2 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 WestLake 7B V2

Model	Likes	Downloads	VRAM
WestLake 10.7B V2 GGUF	25	454	6 GB
WestLake 10.7B V2 EXL2 8.0	1	7	10 GB
WestLake 10.7B V2 EXL2 6.0	1	7	8 GB
WestLake 10.7B V2 EXL2 5.0	1	3	6 GB
WestLake 7B V2 GGUF	20	330	2 GB
WestLake 7B V2 Laser AWQ	1	7	4 GB
WestLake 7B V2 AWQ	4	45	4 GB
WestLake 7B V2 GPTQ	8	5	4 GB
WestLake 7B V2 AWQ	4	7	4 GB

Best Alternatives to WestLake 7B V2

Best Alternatives	Context / RAM	Downloads	Likes
...Nemo Instruct 2407 Abliterated	1000K / 24.5 GB	220	20
MegaBeam Mistral 7B 512K	512K / 14.4 GB	8470	54
SpydazWeb AI HumanAI RP	512K / 14.4 GB	16	1
SpydazWeb AI HumanAI 002	512K / 14.4 GB	18	1
...daz Web AI ChatML 512K Project	512K / 14.5 GB	12	0
MegaBeam Mistral 7B 300K	282K / 14.4 GB	3779	16
MegaBeam Mistral 7B 300K	282K / 14.4 GB	8018	17
Hebrew Mistral 7B 200K	256K / 30 GB	23	15
Astral 256K 7B	250K / 14.4 GB	9	0
Astral 256K 7B V2	250K / 14.4 GB	8	0

Note: green Score (e.g. "73.2") means that the model is better than senseable/WestLake-7B-v2.