EITLEM-Kinetics

Open weights Beijing University of Chemical Technology September 2024

No estimate

No hardware requirements for this model

This model's weights are open, but no parameter count has been published for it. Every memory and speed figure starts from that number, so we would rather show nothing than a fabricated estimate.

On record

Full specification

Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.

Origin

Who built this model, where, and when it was published.

Organisation
Beijing University of Chemical Technology
Organisation type
Academia
Country
China
Published
19 September 2024
Authors
Xiaowei Shen, Ziheng Cui, Jianyu Long, Shiding Zhang, Biqiang Chen, Tianwei Tan

What it does

The problem areas the model was built for. A model can carry several of each.

Domain
Biology
Task
Mutation prediction

Size

How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.

Training data
34,429 tokens

34,429 × 0.8 = 27,543 28,664 × 0.8 = 22,931 13,388 × 0.8 = 10,710 27,543 + 22,931 + 10,710 = 61,184

Availability

Whether you can obtain the model and run it on your own hardware, which is what decides if any of the graphics-card figures on this page apply.

Weights
Open — downloadable
Model access
Open weights (unrestricted)
Training code
Open source

MIT license: https://github.com/XvesS/EITLEM-Kinetics/tree/main

How it is classified

Labels the source dataset applies when tracking notable models, and how confident it is in the entry.

Record confidence
Confident

Sources

Where this record came from and when it was last checked.

Reference
EITLEM-Kinetics: A Deep-Learning Framework for Kinetic Parameter Prediction of Mutant Enzymes
Last updated
28 November 2025

What the numbers mean

Background

EITLEM-Kinetics was published by Beijing University of Chemical Technology, in China, in September 2024. The organisation is categorised as academia.

It works in Biology, and is recorded as doing mutation prediction.

Published weights mean the model runs on your machine rather than someone else's, which is what makes the hardware question below answerable at all.

Training and provenance

Around 34,429 tokens went into training it.

Answers

EITLEM-Kinetics — common questions

01

How many parameters does EITLEM-Kinetics have?

No parameter count has been published for EITLEM-Kinetics, which is why no memory or speed figure appears on this page.

02

Who created EITLEM-Kinetics?

EITLEM-Kinetics was published by Beijing University of Chemical Technology, based in China, categorised as academia.

03

When was EITLEM-Kinetics released?

EITLEM-Kinetics was published in September 2024. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.

04

What is EITLEM-Kinetics used for?

EITLEM-Kinetics works in Biology, and is recorded as handling mutation prediction. A model can carry several of each, so these are the areas it was built for rather than a limit on what it will attempt.

05

Where can I download EITLEM-Kinetics?

The weights for EITLEM-Kinetics are published, though we do not hold a repository link for it. This site calculates hardware requirements rather than hosting model files.

06

What GPU do I need to run EITLEM-Kinetics?

We cannot say. EITLEM-Kinetics has open weights, but no parameter count has been published for it, and every memory and speed calculation starts from that number. We would rather show nothing than a fabricated estimate.

07

Is EITLEM-Kinetics open source?

Its weights are published, so EITLEM-Kinetics can be downloaded and run on your own hardware. Note that open weights is not the same as open source in the full sense — it says nothing about the training data, the training code, or the commercial terms attached.

Source

Original publication

Record last updated 28 November 2025

The other direction

Looking at it from the other side?

This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.