What are the hardware requirements for RIFA Edge 0.6B?

RIFA Edge 0.6B requires approximately 1.2 GB of VRAM and supports a context window of 40K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed RIFA Edge 0.6B and how large is it?

RIFA Edge 0.6B is developed by smshahbaj, a model with 0.6b 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 RIFA Edge 0.6B?

RIFA Edge 0.6B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

RIFA Edge 0.6B by smshahbaj — VRAM 1.2GB, 40K context

Name: RIFA Edge 0.6B
Author: smshahbaj

RIFA Edge 0.6B is an open-source language model by smshahbaj. Features: 0.6b LLM, VRAM: 1.2GB, Context: 40K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.32.

Bangla Bengali Bn Code Coding Conversational En Endpoints compatible Finetuned Gguf Instruct Instruction-tuned Qwen3 Region:us Rifa Rifa-edge Safetensors Secure-coding

Model Card on HF 🤗: https://huggingface.co/smshahbaj/RIFA-Edge-0.6B

RIFA Edge 0.6B Parameters and Internals

LLM Name	RIFA Edge 0.6B
Repository 🤗	https://huggingface.co/smshahbaj/RIFA-Edge-0.6B
Model Size	0.6b
Required VRAM	1.2 GB
Updated	2026-09-02
Maintainer	smshahbaj
Model Type	qwen3
Instruction-Based	Yes
Model Files	1.2 GB
Supported Languages	en bn
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	40960
Model Max Length	40960
Transformers Version	4.51.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	float16
Errors	replace

Rank the RIFA Edge 0.6B 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

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Quipu 0.6B	40K / 1.2 GB	351	4
Supertron2.1 0.6B	40K / 0.8 GB	0	2
Qwen3 0.6B Instruct	40K / 1.5 GB	29	0
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Qwen 0.6B Pythoncode Instruct	32K / 1.2 GB	505	0
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... 0.6B Instruction Finetuned V2	32K / 1.2 GB	17	0
...en3 0.6B Instruction Finetuned	32K / 1.2 GB	49	0