What are the hardware requirements for Sparse0.5 OPT 1.3?

Sparse0.5 OPT 1.3 requires approximately 2.6 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 Sparse0.5 OPT 1.3 and how large is it?

Sparse0.5 OPT 1.3 is developed by shaohang, a model with 1.3b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Sparse0.5 OPT 1.3 perform on standard benchmarks?

Sparse0.5 OPT 1.3 has the following published scores: MMLU 25.6. Compare against reference models on this page or on the LLM Explorer leaderboards.

Sparse0.5 OPT 1.3 by shaohang — VRAM 2.6GB, 2K context

Name: Sparse0.5 OPT 1.3
Author: shaohang

Sparse0.5 OPT 1.3 is an open-source language model by shaohang. Features: 1.3b LLM, VRAM: 2.6GB, Context: 2K, License: apache-2.0, LLM Explorer Score: 0.13, Arc: 27.1, HellaSwag: 48.7, MMLU: 25.6, GSM8K: 0.1.

Endpoints compatible Opt Pytorch Region:us

Model Card on HF 🤗: https://huggingface.co/shaohang/Sparse0.5_OPT-1.3

Sparse0.5 OPT 1.3 Benchmarks

ARC: 27.13 vs 96.7 (so35)^-71.9%

HellaSwag: 48.69 vs 95.3 (gpt4)^-48.9%

MMLU: 25.6 vs 88.3 (so35)^-71%

GSM8K: 0.08 vs 96.4 (so35)^-99.9%

LLME Score: 0.13473

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Sparse0.5 OPT 1.3 (shaohang/Sparse0.5_OPT-1.3)

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Sparse0.5 OPT 1.3 Parameters and Internals

LLM Name	Sparse0.5 OPT 1.3
Repository 🤗	https://huggingface.co/shaohang/Sparse0.5_OPT-1.3
Model Size	1.3b
Required VRAM	2.6 GB
Updated	2026-05-23
Maintainer	shaohang
Model Type	opt
Model Files	2.6 GB
Model Architecture	OPTForCausalLM
License	apache-2.0
Context Length	2048
Model Max Length	2048
Transformers Version	4.29.1
Beginning of Sentence Token	</s>
End of Sentence Token	</s>
Unk Token	</s>
Vocabulary Size	50272
Torch Data Type	float16
Activation Function	relu
Errors	replace

Best Alternatives to Sparse0.5 OPT 1.3

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Note: green Score (e.g. "73.2") means that the model is better than shaohang/Sparse0.5_OPT-1.3.

Rank the Sparse0.5 OPT 1.3 Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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Release v20260328a

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Sparse0.5 OPT 1.3 by shaohang

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Sparse0.5 OPT 1.3 Benchmarks

Sparse0.5 OPT 1.3 Parameters and Internals

Best Alternatives to Sparse0.5 OPT 1.3

Rank the Sparse0.5 OPT 1.3 Capabilities

What open-source LLMs or SLMs are you in search of? 53999 in total.