What are the hardware requirements for Fizik 0.6B Preview?

Fizik 0.6B Preview 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 Fizik 0.6B Preview and how large is it?

Fizik 0.6B Preview is developed by NewstaR, 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.

How does Fizik 0.6B Preview perform on standard benchmarks?

Fizik 0.6B Preview has the following published scores: LMSYS ELO 1418. Compare against reference models on this page or on the LLM Explorer leaderboards.

Fizik 0.6B Preview by NewstaR — VRAM 1.2GB, 40K context

Name: Fizik 0.6B Preview
Author: NewstaR

Fizik 0.6B Preview is an open-source language model by NewstaR. Features: 0.6b LLM, VRAM: 1.2GB, Context: 40K, License: agpl-3.0, Quantized, LLM Explorer Score: 0.32, ELO: 1418.

4bit Autotrain compatible Base model:finetune:unsloth/qw... Base model:unsloth/qwen3-0.6b-... Conversational Dataset:marcuscedricridia/fizi... En Endpoints compatible Pytorch Quantized Qwen3 Region:us Safetensors Sft Trl Unsloth Zh

Model Card on HF 🤗: https://huggingface.co/NewstaR/Fizik-0.6B-Preview

Fizik 0.6B Preview Benchmarks

LMSys ELO 1418 vs 1272 (so35) 11.5%

^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)

Fizik 0.6B Preview Parameters and Internals

LLM Name	Fizik 0.6B Preview
Repository 🤗	https://huggingface.co/NewstaR/Fizik-0.6B-Preview
Base Model(s)	unsloth/Qwen3-0.6B-unsloth-bnb-4bit unsloth/Qwen3-0.6B-unsloth-bnb-4bit
Model Size	0.6b
Required VRAM	1.2 GB
Updated	2025-06-12
Maintainer	NewstaR
Model Type	qwen3
Model Files	1.2 GB 1.2 GB
Supported Languages	en zh
Quantization Type	4bit
Model Architecture	Qwen3ForCausalLM
License	agpl-3.0
Context Length	40960
Model Max Length	40960
Transformers Version	4.51.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
Vocabulary Size	151936
Torch Data Type	float16
Errors	replace

Rank the Fizik 0.6B Preview 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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