What are the hardware requirements for WestLake 10.7B V2 GGUF?

WestLake 10.7B V2 GGUF requires approximately 6.1 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 10.7B V2 GGUF and how large is it?

WestLake 10.7B V2 GGUF is developed by froggeric, a model with 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 WestLake 10.7B V2 GGUF?

WestLake 10.7B V2 GGUF is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

WestLake 10.7B V2 GGUF by froggeric — VRAM 6.1GB, 32K context

Name: WestLake 10.7B V2 GGUF
Author: froggeric

WestLake 10.7B V2 GGUF is an open-source language model by froggeric. Features: 7b LLM, VRAM: 6.1GB, Context: 32K, License: apache-2.0, Quantized, Merged, LLM Explorer Score: 0.12.

Merged Model Base model:quantized:senseable... Base model:senseable/westlake-... En Endpoints compatible Gguf Mistral Q4 Quantized Region:us

Model Card on HF 🤗: https://huggingface.co/froggeric/WestLake-10.7B-v2-GGUF

WestLake 10.7B V2 GGUF Parameters and Internals

Model Type

Role-Play, Text Generation

Use Cases

Areas:

research, commercial applications

Applications:

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

Primary Use Cases:

Role-Play scenarios, Text Generation

Considerations:

Ensure responsible usage and avoid harmful content generation.

Additional Notes

First viable self-merge obtained after extensive testing.

Supported Languages

en (Proficient)

Training Details

Methodology:

Merges various configurations of the WestLake-7B-v2 model using the passthrough merge method.

Context Length:

8192

Input Output

Accepted Modalities:

text

Performance Tips:

Using larger context size than trained can cause problems.

LLM Name	WestLake 10.7B V2 GGUF
Repository 🤗	https://huggingface.co/froggeric/WestLake-10.7B-v2-GGUF
Base Model(s)	WestLake 7B V2 senseable/WestLake-7B-v2
Merged Model	Yes
Model Size	7b
Required VRAM	6.1 GB
Updated	2026-08-06
Maintainer	froggeric
Model Type	mistral
Model Files	6.1 GB 7.4 GB 8.8 GB 11.4 GB
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf\|q4
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.38.1
Vocabulary Size	32000
Torch Data Type	float16

Rank the WestLake 10.7B V2 GGUF 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 WestLake 10.7B V2 GGUF

Best Alternatives	Context / RAM	Downloads	Likes
MegaBeam Mistral 7B 300K Gguf	282K / 5 GB	35	3
MegaBeam Mistral 7B 300K Gguf	282K / 5 GB	34	3
Backrooms Mistral 7B 10e	32K / 14.5 GB	128	0
Mistral 7B Instruct V0.2.gguf	32K / 14.5 GB	17	3
Mistral 7B Instruct V0.2 GGUF	32K / 4.4 GB	26	2
...andle Mistral 7B Instruct V0.2	32K / 14.4 GB	167	0
...andle Dolphin 2.2.1 Mistral 7B	32K / 14.4 GB	96	0
Boptruth Agatha 7B	32K / 14.4 GB	129	0
Mahou 1.2a Mistral 7B	32K / 14.4 GB	33	7
Tamil Mistral 7B Instruct V0.1	32K / 14.8 GB	350	14

Note: green Score (e.g. "73.2") means that the model is better than froggeric/WestLake-10.7B-v2-GGUF.