What are the hardware requirements for Edgecar 1.5B?

Edgecar 1.5B requires approximately 3.1 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Edgecar 1.5B and how large is it?

Edgecar 1.5B is developed by meettttttttttt, a model with 1.5b 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 Edgecar 1.5B?

Edgecar 1.5B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Edgecar 1.5B by meettttttttttt — VRAM 3.1GB, 32K context

Name: Edgecar 1.5B
Author: meettttttttttt

Edgecar 1.5B is an open-source language model by meettttttttttt. Features: 1.5b LLM, VRAM: 3.1GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.3.

Automotive Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-1.5b-i... Conversational Edge-ai En Endpoints compatible Instruct On-device Qwen2 Region:us Safetensors Semantic-parsing Text-to-command Vehicle-data

Model Card on HF 🤗: https://huggingface.co/meettttttttttt/edgecar-1.5b

Edgecar 1.5B Parameters and Internals

LLM Name	Edgecar 1.5B
Repository 🤗	https://huggingface.co/meettttttttttt/edgecar-1.5b
Base Model(s)	Qwen/Qwen2.5-1.5B-Instruct Qwen/Qwen2.5-1.5B-Instruct
Model Size	1.5b
Required VRAM	3.1 GB
Updated	2026-10-31
Maintainer	meettttttttttt
Model Type	qwen2
Instruction-Based	Yes
Model Files	3.1 GB
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	5.21.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Errors	replace

Rank the Edgecar 1.5B 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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