What are the hardware requirements for Circuit Sparsity?

Circuit Sparsity requires approximately 1.7 GB of VRAM and supports a context window of 1K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Circuit Sparsity and how large is it?

Circuit Sparsity is developed by openai, a model with 419.1m 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 Circuit Sparsity?

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

Circuit Sparsity by openai — VRAM 1.7GB, 1K context

Name: Circuit Sparsity
Author: openai

Circuit Sparsity is an open-source language model by openai. Features: 419.1m LLM, VRAM: 1.7GB, Context: 1K, License: apache-2.0, LLM Explorer Score: 0.25.

Circuitgpt Custom code Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/openai/circuit-sparsity

Circuit Sparsity Parameters and Internals

LLM Name	Circuit Sparsity
Repository 🤗	https://huggingface.co/openai/circuit-sparsity
Model Size	419.1m
Required VRAM	1.7 GB
Updated	2026-08-08
Maintainer	openai
Model Type	circuitgpt
Model Files	1.7 GB
Model Architecture	CircuitGPTForCausalLM
License	apache-2.0
Context Length	1024
Model Max Length	1024
Transformers Version	4.49.0
Is Biased	1
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	2048
Torch Data Type	float32

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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