What are the hardware requirements for Seahorse 350M?

Seahorse 350M requires approximately 1.4 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Seahorse 350M and how large is it?

Seahorse 350M is developed by TitleOS, a model with 350m 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 Seahorse 350M?

Seahorse 350M is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Seahorse 350M by TitleOS — VRAM 1.4GB, 2K context

Name: Seahorse 350M
Author: TitleOS

Seahorse 350M is an open-source language model by TitleOS. Features: 350m LLM, VRAM: 1.4GB, Context: 2K, License: other, LLM Explorer Score: 0.07.

Arxiv:2205.01068 Dataset:psmathur/alpaca orca En Endpoints compatible Opt Pytorch Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/TitleOS/Seahorse-350m

Seahorse 350M Parameters and Internals

Model Type

text generation

Use Cases

Limitations:

Potential biases include gender, profession, race and religion.

Training Details

Data Sources:

psmathur/alpaca_orca

Methodology:

Finetuned on the Orca dataset formatted to the Alpaca style

LLM Name	Seahorse 350M
Repository 🤗	https://huggingface.co/TitleOS/Seahorse-350m
Model Size	350m
Required VRAM	1.4 GB
Updated	2026-07-28
Maintainer	TitleOS
Model Type	opt
Model Files	0.4 GB: 1-of-4 0.4 GB: 2-of-4 0.4 GB: 3-of-4 0.2 GB: 4-of-4 0.4 GB: 1-of-4 0.4 GB: 2-of-4 0.4 GB: 3-of-4 0.2 GB: 4-of-4
Supported Languages	en
Model Architecture	OPTForCausalLM
License	other
Context Length	2048
Model Max Length	2048
Transformers Version	4.27.0
Beginning of Sentence Token	</s>
End of Sentence Token	</s>
Unk Token	</s>
Vocabulary Size	50272
Torch Data Type	float32
Activation Function	relu
Errors	replace

Rank the Seahorse 350M 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 Seahorse 350M

Best Alternatives	Context / RAM	Downloads	Likes
Opt 350M	2K / 0.7 GB	198521	149
Opt Mini Dataset 0	2K / 0.7 GB	8	0
Facebook Opt 350M SFT Korz14	2K / 0.7 GB	12	0
Temp Model Sft	2K / 1.3 GB	7	0
Gpt350 Chat S V0	2K / 0.7 GB	6	0
Gpt350 Chat S V0 1	2K / 0.7 GB	5	0
Dadjokes Tuned Opt	2K / 1.3 GB	8	2
Pygmalion 350M	2K / 1.3 GB	348	54
Rockyalquimista888	2K / 1.3 GB	8	0
Remedycure	2K / 1.3 GB	6	0

Note: green Score (e.g. "73.2") means that the model is better than TitleOS/Seahorse-350m.