What are the hardware requirements for Sarath Om 1.0?

Sarath Om 1.0 requires approximately 3.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Sarath Om 1.0 and how large is it?

Sarath Om 1.0 is developed by sarath-om, a model with 1.5b 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 Sarath Om 1.0?

Sarath Om 1.0 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Sarath Om 1.0 by sarath-om — VRAM 3.1GB

Name: Sarath Om 1.0
Author: sarath-om

Sarath Om 1.0 is an open-source language model by sarath-om. Features: 1.5b LLM, VRAM: 3.1GB, Merged, LLM Explorer Score: 0.29.

Merged Model Conversational Endpoints compatible Image-text-to-text Lora Qwen2 Reasoning Region:us Safetensors Sarath-om Thinking Tools Vision

Model Card on HF 🤗: https://huggingface.co/sarath-om/sarath_om-1.0

Sarath Om 1.0 Parameters and Internals

LLM Name	Sarath Om 1.0
Repository 🤗	https://huggingface.co/sarath-om/sarath_om-1.0
Merged Model	Yes
Model Size	1.5b
Required VRAM	3.1 GB
Updated	2026-10-28
Maintainer	sarath-om
Model Files	0.0 GB 3.1 GB
Model Architecture	AutoModelForCausalLM
Model Max Length	131072
Is Biased	none
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	gate_proj\|up_proj\|down_proj\|q_proj\|k_proj\|v_proj\|o_proj
LoRA Alpha	32
LoRA Dropout	0.05
R Param	16
Errors	replace

Rank the Sarath Om 1.0 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

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Qwen25 D2l Merged	0K / 0.1 GB	356	1
Iz Instruct	0K / 0.1 GB	81	1
AceMath 1.5B Instruct 1epoch	0K / 0.1 GB	7	0
Acemath 200	0K / 0.1 GB	12	0
Qwen First Aid Medium	0K / 1.9 GB	0	0
MeoinGTS1.5 1.5B	0K / 1 GB	147	0
OpenThink	0K / 1.1 GB	880	0