What are the hardware requirements for Nock Coder 1.5B?

Nock Coder 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 Nock Coder 1.5B and how large is it?

Nock Coder 1.5B is developed by Nock-AI, 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 Nock Coder 1.5B?

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

Nock Coder 1.5B by Nock-AI — VRAM 3.1GB, 32K context

Name: Nock Coder 1.5B
Author: Nock-AI

Nock Coder 1.5B is an open-source language model by Nock-AI. Features: 1.5b LLM, VRAM: 3.1GB, Context: 32K, License: apache-2.0, Instruction-Based, Code Generating, LLM Explorer Score: 0.32.

Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-coder-... Code Codegen Conversational En Endpoints compatible Instruct Lora Qwen2 Region:us Safetensors Solidity

Model Card on HF 🤗: https://huggingface.co/Nock-AI/nock-coder-1.5b

Nock Coder 1.5B Parameters and Internals

LLM Name	Nock Coder 1.5B
Repository 🤗	https://huggingface.co/Nock-AI/nock-coder-1.5b
Base Model(s)	Qwen/Qwen2.5-Coder-1.5B-Instruct Qwen/Qwen2.5-Coder-1.5B-Instruct
Model Size	1.5b
Required VRAM	3.1 GB
Updated	2026-10-13
Maintainer	Nock-AI
Model Type	qwen2
Instruction-Based	Yes
Model Files	3.1 GB
Supported Languages	en
Generates Code	Yes
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	5.19.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Errors	replace

Rank the Nock Coder 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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