What are the hardware requirements for Securin LLM V2.5 Qwen 1.5B?

Securin LLM V2.5 Qwen 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 Securin LLM V2.5 Qwen 1.5B and how large is it?

Securin LLM V2.5 Qwen 1.5B is developed by securin, 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 Securin LLM V2.5 Qwen 1.5B?

Securin LLM V2.5 Qwen 1.5B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Securin LLM V2.5 Qwen 1.5B by securin — VRAM 3.1GB, 32K context

Name: Securin LLM V2.5 Qwen 1.5B
Author: securin

Securin LLM V2.5 Qwen 1.5B is an open-source language model by securin. Features: 1.5b LLM, VRAM: 3.1GB, Context: 32K, Fine-Tuned, Code Generating, Merged, LLM Explorer Score: 0.17.

Merged Model Arxiv:2306.01708 Base model:qwen/qwen2.5-coder-... Base model:qwen/qwen2.5-coder-... Base model:securin/qwen finetu... Codegen Endpoints compatible Finetuned Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/securin/Securin-LLM-V2.5-Qwen-1.5B

Securin LLM V2.5 Qwen 1.5B Parameters and Internals

LLM Name	Securin LLM V2.5 Qwen 1.5B
Repository 🤗	https://huggingface.co/securin/Securin-LLM-V2.5-Qwen-1.5B
Base Model(s)	Qwen/Qwen2.5-Coder-1.5B-Instruct Qwen Finetune Intermediate Qwen/Qwen2.5-Coder-1.5B Qwen/Qwen2.5-Coder-1.5B-Instruct securin/qwen_finetune_intermediate Qwen/Qwen2.5-Coder-1.5B
Merged Model	Yes
Model Size	1.5b
Required VRAM	3.1 GB
Updated	2026-08-05
Maintainer	securin
Model Type	qwen2
Model Files	3.1 GB: 1-of-1
Generates Code	Yes
Model Architecture	Qwen2ForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.46.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|PAD_TOKEN\|>
Vocabulary Size	151666
Torch Data Type	bfloat16
Errors	replace

Rank the Securin LLM V2.5 Qwen 1.5B 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 Securin LLM V2.5 Qwen 1.5B

Best Alternatives	Context / RAM	Downloads	Likes
Merge Cord V1	128K / 3.1 GB	155	1
Replete Coder Qwen2 1.5B	128K / 3.1 GB	233	23
Coder O1 Mini Reasoning	32K / 3.1 GB	644	0
Pulsar Coder 1.5B	32K / 3.1 GB	13	0
Qwen2.5 Coder 1.5B Instruct	32K / 3.1 GB	695585	134
Mythos Qwen 1.5B Final	32K / 3.1 GB	104	1
Microcoder 1.5B	32K / 3.1 GB	20	4
Qwen2.5 Coder 1.5B	32K / 3.1 GB	197356	95
Qwen2.5 Coder 1.5B Instruct	32K / 3.1 GB	69796	6
...n2.5 Coder Draft 1.5B Instruct	32K / 3.1 GB	7	0

Note: green Score (e.g. "73.2") means that the model is better than securin/Securin-LLM-V2.5-Qwen-1.5B.