What are the hardware requirements for Soro?

Soro requires approximately 5.8 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Soro and how large is it?

Soro is developed by zaddyzaddy, a model with 8b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Soro perform on standard benchmarks?

Soro has the following published scores: LMSYS ELO 1367. Compare against reference models on this page or on the LLM Explorer leaderboards.

Soro by zaddyzaddy — VRAM 5.8GB

Name: Soro
Author: zaddyzaddy

Soro is an open-source language model by zaddyzaddy. Features: 8b LLM, VRAM: 5.8GB, Quantized, LLM Explorer Score: 0.27, ELO: 1367.

Arxiv:1910.09700 4bit 8-bit Adapter Base model:adapter:unsloth/lla... Base model:unsloth/llama-3-8b-... Endpoints compatible Finetuned Lora Peft Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/zaddyzaddy/soro

Soro Benchmarks

LMSys ELO 1367 vs 1272 (so35) 7.5%

^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)

Soro Parameters and Internals

LLM Name	Soro
Repository 🤗	https://huggingface.co/zaddyzaddy/soro
Base Model(s)	Llama 3 8B Bnb 4bit unsloth/llama-3-8b-bnb-4bit
Model Size	8b
Required VRAM	5.8 GB
Updated	2026-08-06
Maintainer	zaddyzaddy
Model Files	0.2 GB 4.7 GB: 1-of-2 1.1 GB: 2-of-2
Quantization Type	4bit
Model Architecture	Adapter
Model Max Length	8192
Is Biased	none
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|reserved_special_token_250\|>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	down_proj\|up_proj\|gate_proj\|k_proj\|v_proj\|q_proj\|o_proj
LoRA Alpha	16
LoRA Dropout	0
R Param	16

Rank the Soro 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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