What are the hardware requirements for RWKV7 G1j 2.9B 20260831?

RWKV7 G1j 2.9B 20260831 requires approximately 5.9 GB of VRAM and supports a context window of 16K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed RWKV7 G1j 2.9B 20260831 and how large is it?

RWKV7 G1j 2.9B 20260831 is developed by fla-hub, a model with 2.9b 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 RWKV7 G1j 2.9B 20260831?

RWKV7 G1j 2.9B 20260831 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

RWKV7 G1j 2.9B 20260831 by fla-hub — VRAM 5.9GB, 16K context

Name: RWKV7 G1j 2.9B 20260831
Author: fla-hub

RWKV7 G1j 2.9B 20260831 is an open-source language model by fla-hub. Features: 2.9b LLM, VRAM: 5.9GB, Context: 16K, License: apache-2.0, LLM Explorer Score: 0.28.

Arxiv:2503.14456 Ar Base model:blinkdl/rwkv7-g1 Base model:finetune:blinkdl/rw... Conversational Dataset:bigcode/starcoderdata Dataset:cerebras/slimpajama-62... Dataset:eleutherai/pile Dataset:huggingfacefw/fineweb-... Dataset:mlfoundations/dclm-bas... Dataset:oscar-corpus/oscar-230... De En Endpoints compatible Es Fla Fr It Ja Ko Pt Recurrent Region:us Ru Rwkv Rwkv7 Safetensors Vi Zh

Model Card on HF 🤗: https://huggingface.co/fla-hub/RWKV7-G1j-2.9B-20260831

RWKV7 G1j 2.9B 20260831 Parameters and Internals

LLM Name	RWKV7 G1j 2.9B 20260831
Repository 🤗	https://huggingface.co/fla-hub/RWKV7-G1j-2.9B-20260831
Base Model(s)	BlinkDL/rwkv7-g1 BlinkDL/rwkv7-g1
Model Size	2.9b
Required VRAM	5.9 GB
Updated	2026-10-31
Maintainer	fla-hub
Model Type	rwkv7
Model Files	5.9 GB
Supported Languages	en zh fr es de pt ru it ja ko vi ar
Model Architecture	RWKV7ForCausalLM
License	apache-2.0
Context Length	16384
Model Max Length	16384
Transformers Version	4.50.2
Tokenizer Class	Rwkv7Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	65536
Torch Data Type	bfloat16

Rank the RWKV7 G1j 2.9B 20260831 capabilities

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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

Best Alternatives to RWKV7 G1j 2.9B 20260831

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RWKV7 Goose World3 2.9B HF	2K / 5.9 GB	574	18