What are the hardware requirements for Chatml Test?

Chatml Test requires approximately 2.1 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Chatml Test and how large is it?

Chatml Test is developed by AlekseyKorshuk, a model with 1b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Chatml Test perform on standard benchmarks?

Chatml Test has the following published scores: LMSYS ELO 1449. Compare against reference models on this page or on the LLM Explorer leaderboards.

Chatml Test by AlekseyKorshuk — VRAM 2.1GB, 2K context

Name: Chatml Test
Author: AlekseyKorshuk

Chatml Test is an open-source language model by AlekseyKorshuk. Features: 1b LLM, VRAM: 2.1GB, Context: 2K, License: apache-2.0, LLM Explorer Score: 0.21, ELO: 1449.

Endpoints compatible Generated from trainer Gpt neox Pytorch Region:us

Model Card on HF 🤗: https://huggingface.co/AlekseyKorshuk/chatml-test

Chatml Test Benchmarks

LMSys ELO 1449 vs 1272 (so35) 13.9%

^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)

Chatml Test Parameters and Internals

Additional Notes

More information needed on model description, intended uses, limitations, and training/evaluation data.

Training Details

Methodology:

Fine-tuning

Hardware Used:

multi-GPU

LLM Name	Chatml Test
Repository 🤗	https://huggingface.co/AlekseyKorshuk/chatml-test
Model Size	1b
Required VRAM	2.1 GB
Updated	2026-08-25
Maintainer	AlekseyKorshuk
Model Type	gpt_neox
Model Files	2.1 GB 0.0 GB
Model Architecture	GPTNeoXForCausalLM
License	apache-2.0
Context Length	2048
Model Max Length	2048
Transformers Version	4.28.0
Tokenizer Class	GPTNeoXTokenizer
Vocabulary Size	50279
Torch Data Type	float16

Rank the Chatml Test 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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