What are the hardware requirements for Starstreak 7B Alpha?

Starstreak 7B Alpha 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 Starstreak 7B Alpha and how large is it?

Starstreak 7B Alpha is developed by azale-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.

Where can I download or evaluate Starstreak 7B Alpha?

Starstreak 7B Alpha is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Starstreak 7B Alpha by azale-ai — VRAM 14.4GB, 32K context

Name: Starstreak 7B Alpha
Author: azale-ai

Starstreak 7B Alpha is an open-source language model by azale-ai. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: cc0-1.0, LLM Explorer Score: 0.09.

Conversational Dataset:graelo/wikipedia Dataset:uonlp/culturax En Endpoints compatible Id Indonesian Jv Mistral Ms Multilingual Pytorch Region:us Safetensors Sharded Su Tensorflow

Model Card on HF 🤗: https://huggingface.co/azale-ai/Starstreak-7b-alpha

Starstreak 7B Alpha Parameters and Internals

Model Type

language model, multilingual

Use Cases

Areas:

multilingual applications, research

Primary Use Cases:

text generation in multiple languages including traditional Indonesian languages

Limitations:

Cultural and contextual biases

Additional Notes

The name "Starstreak" is inspired by the Starstreak missile, indicating speed and efficiency.

Supported Languages

English (Fluent), Indonesian (Fluent), Achinese (Basic), Balinese (Basic), Banjar (Basic), Basa Banyumasan (Basic), Buginese (Basic), Gorontalo (Basic), Javanese (Basic), Maduranese (Basic), Minangkabau (Basic), Sundanese (Basic), Malay (Fluent), Nias (Basic), Tetum (Basic)

Training Details

Data Sources:

graelo/wikipedia, uonlp/CulturaX

Methodology:

Finetuned with QLoRA technique

Context Length:

2048

Input Output

Accepted Modalities:

text

Performance Tips:

Innovate with contextualized prompts for better performance in language-based tasks.

LLM Name	Starstreak 7B Alpha
Repository 🤗	https://huggingface.co/azale-ai/Starstreak-7b-alpha
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-04-24
Maintainer	azale-ai
Model Type	mistral
Model Files	1.9 GB: 1-of-8 1.9 GB: 2-of-8 2.0 GB: 3-of-8 1.9 GB: 4-of-8 2.0 GB: 5-of-8 1.9 GB: 6-of-8 2.0 GB: 7-of-8 0.8 GB: 8-of-8 1.9 GB: 1-of-8 1.9 GB: 2-of-8 2.0 GB: 3-of-8 1.9 GB: 4-of-8 2.0 GB: 5-of-8 1.9 GB: 6-of-8 2.0 GB: 7-of-8 0.8 GB: 8-of-8
Supported Languages	en id jv su ms
Model Architecture	MistralForCausalLM
License	cc0-1.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.35.0.dev0
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Starstreak 7B Alpha 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 Starstreak 7B Alpha

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 azale-ai/Starstreak-7b-alpha.