What are the hardware requirements for RWKV 4 World 1.5B?

RWKV 4 World 1.5B requires approximately 3.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed RWKV 4 World 1.5B and how large is it?

RWKV 4 World 1.5B is developed by StarRing2022, 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 RWKV 4 World 1.5B?

RWKV 4 World 1.5B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

RWKV 4 World 1.5B by StarRing2022 — VRAM 3.2GB

Name: RWKV 4 World 1.5B
Author: StarRing2022

RWKV 4 World 1.5B is an open-source language model by StarRing2022. Features: 1.5b LLM, VRAM: 3.2GB, License: apache-2.0, LLM Explorer Score: 0.07.

Endpoints compatible Pytorch Region:us Rwkv

Model Card on HF 🤗: https://huggingface.co/StarRing2022/RWKV-4-World-1.5B

RWKV 4 World 1.5B Parameters and Internals

Model Type

Causal Language Model

Use Cases

Areas:

Research, Commercial Applications

Applications:

Conversational Agents, Text Generation

Primary Use Cases:

Question Answering

Additional Notes

Bugfix applied to Forward RWKVOutput for improved handling of last_hidden_state.

Supported Languages

primary (Chinese), additional ()

Input Output

Input Format:

Encoded question text as input

Accepted Modalities:

text

Output Format:

Generated text tokens

LLM Name	RWKV 4 World 1.5B
Repository 🤗	https://huggingface.co/StarRing2022/RWKV-4-World-1.5B
Model Size	1.5b
Required VRAM	3.2 GB
Updated	2026-07-31
Maintainer	StarRing2022
Model Type	rwkv
Model Files	3.2 GB
Model Architecture	AutoModel
License	apache-2.0
Transformers Version	4.29.0
Vocabulary Size	65536

Rank the RWKV 4 World 1.5B 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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Note: green Score (e.g. "73.2") means that the model is better than StarRing2022/RWKV-4-World-1.5B.