What are the hardware requirements for Vector L1 4B?

Vector L1 4B requires approximately 8.1 GB of VRAM and supports a context window of 256K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Vector L1 4B and how large is it?

Vector L1 4B is developed by MikaLabs, a model with 4b 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 Vector L1 4B?

Vector L1 4B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Vector L1 4B by MikaLabs — VRAM 8.1GB, 256K context

Name: Vector L1 4B
Author: MikaLabs

Vector L1 4B is an open-source language model by MikaLabs. Features: 4b LLM, VRAM: 8.1GB, Context: 256K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.24.

Base model:finetune:unsloth/qw... Base model:unsloth/qwen3-4b-in... Conversational Education En Instruct Lesson-planning Qwen3 Region:us Safetensors Sharded Teaching Tensorflow Worksheet-generation

Model Card on HF 🤗: https://huggingface.co/MikaLabs/Vector-L1-4B

Vector L1 4B Parameters and Internals

LLM Name	Vector L1 4B
Repository 🤗	https://huggingface.co/MikaLabs/Vector-L1-4B
Base Model(s)	Qwen3 4B Instruct 2507 unsloth/Qwen3-4B-Instruct-2507
Model Size	4b
Required VRAM	8.1 GB
Updated	2026-07-27
Maintainer	MikaLabs
Model Type	qwen3
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-2 3.1 GB: 2-of-2
Supported Languages	en
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|PAD_TOKEN\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Vector L1 4B 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 Vector L1 4B

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3 4B Instruct 2507	256K / 8.1 GB	3109972	911
FastContext 1.0 4B SFT	256K / 8.1 GB	5735	357
Fable Traces	256K / 8.1 GB	342	210
FastContext 1.0 4B RL	256K / 8.1 GB	4559	61
Qwen3 4B Cuad Extractor	256K / 8.1 GB	322	1
Qwen3 4B Instruct 2507 FP8	256K / 5.2 GB	1100744	78
Qwen Fine Tuned	256K / 8 GB	293	1
Qwen3 4B Sft Prm	256K / 17.6 GB	602	0
...pt Full Qwen3 4b Instruct 2507	256K / 8 GB	365	1
Luck Qwen3 4B Code FineTune	256K / 8.1 GB	132	1

Note: green Score (e.g. "73.2") means that the model is better than MikaLabs/Vector-L1-4B.