What are the hardware requirements for Gmcoder?

Gmcoder requires approximately 5.6 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gmcoder and how large is it?

Gmcoder is developed by emperorofrome, a model with 9b 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 Gmcoder?

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

Gmcoder by emperorofrome — VRAM 5.6GB

Name: Gmcoder
Author: emperorofrome

Gmcoder is an open-source language model by emperorofrome. Features: 9b LLM, VRAM: 5.6GB, License: mit, Quantized, LLM Explorer Score: 0.38.

9b Base model:merge:ornith-ai/orn... Base model:merge:qwen/qwen3.5-... Base model:ornith-ai/ornith-1.... Base model:qwen/qwen3.5-9b Code Coding Conversational En Endpoints compatible Gguf Merge Quantized Qwen3 5 Reasoning Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/emperorofrome/Gmcoder

Gmcoder Parameters and Internals

LLM Name	Gmcoder
Repository 🤗	https://huggingface.co/emperorofrome/Gmcoder
Base Model(s)	Qwen/Qwen3.5-9B ornith-ai/Ornith-1.5-9B Qwen/Qwen3.5-9B ornith-ai/Ornith-1.5-9B
Model Size	9b
Required VRAM	5.6 GB
Updated	2026-10-01
Maintainer	emperorofrome
Model Type	qwen3_5
Model Files	5.6 GB 9.8 GB 18.8 GB
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	Qwen3_5ForConditionalGeneration
License	mit
Model Max Length	262144
Transformers Version	5.5.0
Tokenizer Class	TokenizersBackend
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Gmcoder 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

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