What are the hardware requirements for 558434?

558434 requires approximately 16.1 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed 558434 and how large is it?

558434 is developed by Sela223, a model with 8b 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 558434?

558434 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

558434 by Sela223 — VRAM 16.1GB, 128K context

Name: 558434
Author: Sela223

558434 is an open-source language model by Sela223. Features: 8b LLM, VRAM: 16.1GB, Context: 128K, Quantized, LLM Explorer Score: 0.19.

Conversational Endpoints compatible Gguf Llama Q5 Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Sela223/558434

558434 Parameters and Internals

LLM Name	558434
Repository 🤗	https://huggingface.co/Sela223/558434
Model Size	8b
Required VRAM	16.1 GB
Updated	2026-07-20
Maintainer	Sela223
Model Type	llama
Model Files	5.7 GB 5.0 GB: 1-of-4 5.0 GB: 2-of-4 4.9 GB: 3-of-4 1.2 GB: 4-of-4
GGUF Quantization	Yes
Quantization Type	q5\|gguf\|q5_k
Model Architecture	LlamaForCausalLM
Context Length	131072
Model Max Length	131072
Transformers Version	4.53.2
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	128256
Torch Data Type	bfloat16

Rank the 558434 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

Best Alternatives to 558434

Best Alternatives	Context / RAM	Downloads	Likes
10K V6	1024K / 16.1 GB	5	0
...truct Gradient 1048K IMat GGUF	1024K / 2 GB	650	6
...B Instruct Gradient 1048K GGUF	1024K / 3.2 GB	445	3
Unhinged Llama3 8B 524K	512K / 26.5 GB	25	0
Llama 3 8B Instruct 262K GGUF	256K / 3.2 GB	208	2
Dolphin3 Cyber 8B GGUF	128K / 3.2 GB	456	1
Dolphin3 Cyber 8B GGUF	128K / 3.2 GB	59950	150
Grok Oss Apollyon 8B	128K / 16.1 GB	3449	8
Delentia Slm Jitna V0.4	128K / 16.1 GB	413	1
Grok Oss Revenant 8B	128K / 16.1 GB	324	0

Note: green Score (e.g. "73.2") means that the model is better than Sela223/558434.