Vector-L1-4B is an open language model built by MikaLabs to help teachers create classroom materials — differentiated worksheets, lesson plans, quizzes, mark schemes, misconception guides, and tailored explanations across Maths and the Sciences.
The "L1" denotes Light, version 1 — the first and smallest member of a planned Vector model family. It is designed to run on modest consumer hardware so that schools and individual teachers can use it locally and offline.
Vector-L1-4B identifies itself as Vector, a teaching assistant by MikaLabs.
Intended Use
Vector-L1-4B is intended as a teaching-assistant model for educators. It is good at:
Differentiated worksheets — multi-tier (support / core / extension) question sets that show genuine difficulty progression.
Mark schemes — with method marks (M) and answer marks (A) shown separately.
Misconception guides — listing common, subject-specific student misconceptions and how to address them.
Lesson plans — structured with objectives, starters, main activities, and plenaries.
Mixed-format questions — short answer, true/false, fill-in-the-blank, calculation, explain-your-reasoning.
Concept explanations — pitched to a specified age or ability level.
Following formatting and structural instructions — e.g. "no multiple choice", "output as a markdown table", "give three tiers".
Out of Scope / Not Intended For
High-stakes or unsupervised assessment without a human teacher reviewing the output.
A substitute for a qualified teacher's judgement.
General-purpose chat, coding, or non-educational tasks (it is specialised).
Subjects outside Maths and the Sciences (coverage is weaker elsewhere).
Strengths
Vector-L1-4B punches well above its size as a teaching assistant. It excels at:
Differentiated worksheets with genuinely distinct support / core / extension tiers and real difficulty progression.
Professional mark schemes that separate method marks (M) from answer marks (A), the way real exam marking works.
Subject-specific misconception guides — identifying the actual errors students make on a topic and how to address them.
Structured lesson plans with clear objectives, starters, main activities, and plenaries.
A wide range of question formats — short answer, true/false with justification, fill-in-the-blank, calculation, and explain-your-reasoning — without defaulting to multiple choice.
Strong instruction-following on complex, multi-part requests (e.g. "three tiers, a mark scheme, misconceptions, no multiple choice, output as markdown").
Accurate level calibration, pitching difficulty appropriately for the age or ability you specify.
Clean, ready-to-use output — it produces the resource you asked for directly, without conversational filler.
A Note on Scale
Vector-L1-4B is a compact 4-billion-parameter model designed to run on everyday school hardware. It is built for school and secondary-level teaching, not university or research-level material. On very hard problems it may occasionally make mistakes, so — as with any AI tool — answer keys and factual content should be reviewed by a teacher before use with students.
How to Use
Example (transformers):
python
1from transformers import AutoModelForCausalLM, AutoTokenizer
23model_id ="MikaLabs/Vector-L1-4B"4tok = AutoTokenizer.from_pretrained(model_id)5model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")67messages =[8{"role":"user","content":"Create a differentiated worksheet on Pythagoras' theorem for a mixed-ability class. Three tiers with 3 questions each, a mark scheme with method and answer marks, and a list of common misconceptions. No multiple choice."}9]10inputs = tok.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device)11out = model.generate(inputs, max_new_tokens=2048, temperature=0.7)12print(tok.decode(out[0][inputs.shape[-1]:], skip_special_tokens=True))
Recommended generation settings: temperature 0.7, top_p 0.8.
Ethical Considerations & Responsible Use
Outputs — especially answer keys and scientific facts — must be reviewed by a qualified educator before use with students.
It is an assistant, not an authority.
It is specialised for English-language Maths and Science teaching; quality and accuracy degrade outside that scope.
Citation
@misc{vector-l1-4b,
title = {Vector-L1-4B: An Open Teaching-Assistant Model},
author = {MikaLabs},
year = {2026},
url = {https://huggingface.co/MikaLabs/Vector-L1-4B}
}
Acknowledgements
Built on Qwen3-4B-Instruct-2507 by the Qwen team, used under the Apache 2.0 license.
