What are the hardware requirements for Starling LM 7B Beta AWQ?

Starling LM 7B Beta AWQ requires approximately 4.2 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Starling LM 7B Beta AWQ and how large is it?

Starling LM 7B Beta AWQ is developed by solidrust, 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 Starling LM 7B Beta AWQ perform on standard benchmarks?

Starling LM 7B Beta AWQ has the following published scores: MMLU 65.3. Compare against reference models on this page or on the LLM Explorer leaderboards.

Starling LM 7B Beta AWQ by solidrust — VRAM 4.2GB, 8K context

Name: Starling LM 7B Beta AWQ
Author: solidrust

Starling LM 7B Beta AWQ is an open-source language model by solidrust. Features: 7b LLM, VRAM: 4.2GB, Context: 8K, License: apache-2.0, Quantized, LLM Explorer Score: 0.12, Arc: 67.9, HellaSwag: 83.6, MMLU: 65.3, GSM8K: 65.7.

Arxiv:1909.08593 4-bit Autotrain compatible Awq Base model:nexusflow/starling-... Base model:quantized:nexusflow... Chatml Conversational Dataset:berkeley-nest/nectar En Endpoints compatible Mistral Quantized Region:us Reward model Rlaif Rlhf Safetensors

Model Card on HF 🤗: https://huggingface.co/solidrust/Starling-LM-7B-beta-AWQ

Starling LM 7B Beta AWQ Parameters and Internals

LLM Name	Starling LM 7B Beta AWQ
Repository 🤗	https://huggingface.co/solidrust/Starling-LM-7B-beta-AWQ
Model Name	Starling-LM-7B-beta
Model Creator	Nexusflow
Base Model(s)	Starling LM 7B Beta Nexusflow/Starling-LM-7B-beta
Model Size	7b
Required VRAM	4.2 GB
Updated	2026-07-19
Maintainer	solidrust
Model Type	mistral
Model Files	4.2 GB
Supported Languages	en
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	8192
Model Max Length	8192
Transformers Version	4.39.1
Tokenizer Class	LlamaTokenizer
Padding Token	<\|end_of_turn\|>
Vocabulary Size	32002
Torch Data Type	float16

Rank the Starling LM 7B Beta AWQ capabilities

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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 Starling LM 7B Beta AWQ

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Mistral 7B Instruct V0.2 AWQ	32K / 4.2 GB	6	0
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Mistral 7B Instruct V0.3 AWQ	32K / 4.2 GB	5633	10
Mistral 7B Instruct V0.1 AWQ	32K / 4.2 GB	15461	2
Ghost 7B Alpha AWQ	32K / 4.2 GB	14	0
Tess 7B V2.0 AWQ	32K / 4.2 GB	1	1
...reeze 7B 32K Instruct V1.0 AWQ	32K / 4.7 GB	9	0
Breeze 7B Instruct V1.0 AWQ	32K / 4.6 GB	5	0
OpenHermes 2.5 Mistral 7B AWQ	32K / 4.2 GB	23691	21
NSFW DPO Noromaid 7B AWQ	32K / 4.2 GB	206	2

Note: green Score (e.g. "73.2") means that the model is better than solidrust/Starling-LM-7B-beta-AWQ.