What are the hardware requirements for Saba1.5 1.7B?

Saba1.5 1.7B requires approximately 3.5 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Saba1.5 1.7B and how large is it?

Saba1.5 1.7B is developed by Sakalti, a model with 1.7b 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 Saba1.5 1.7B?

Saba1.5 1.7B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Saba1.5 1.7B by Sakalti — VRAM 3.5GB, 128K context

Name: Saba1.5 1.7B
Author: Sakalti

Saba1.5 1.7B is an open-source language model by Sakalti. Features: 1.7b LLM, VRAM: 3.5GB, Context: 128K, License: apache-2.0, Merged, LLM Explorer Score: 0.16.

Merged Model Base model:finetune:sakalti/sa... Base model:sakalti/saba1.5-pro Conversational Endpoints compatible Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Sakalti/Saba1.5-1.7B

Saba1.5 1.7B Parameters and Internals

LLM Name	Saba1.5 1.7B
Repository 🤗	https://huggingface.co/Sakalti/Saba1.5-1.7B
Base Model(s)	Sakalti/Saba1.5-Pro Sakalti/Saba1.5-Pro
Merged Model	Yes
Model Size	1.7b
Required VRAM	3.5 GB
Updated	2026-08-03
Maintainer	Sakalti
Model Type	qwen2
Model Files	3.5 GB: 1-of-1
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	131072
Model Max Length	131072
Transformers Version	4.46.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Saba1.5 1.7B 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 Saba1.5 1.7B

Best Alternatives	Context / RAM	Downloads	Likes
SJT 1.7B	128K / 3.4 GB	20	0

Note: green Score (e.g. "73.2") means that the model is better than Sakalti/Saba1.5-1.7B.