What are the hardware requirements for PentaCoder 9B?

PentaCoder 9B requires approximately 17.9 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 PentaCoder 9B and how large is it?

PentaCoder 9B is developed by pragmaticcs, 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 PentaCoder 9B?

PentaCoder 9B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

PentaCoder 9B by pragmaticcs — VRAM 17.9GB, 256K context

Name: PentaCoder 9B
Author: pragmaticcs

PentaCoder 9B is an open-source language model by pragmaticcs. Features: 9b LLM, VRAM: 17.9GB, Context: 256K, License: apache-2.0, LLM Explorer Score: 0.32.

Arxiv:2403.19522 Arxiv:2406.11617 Agentic Base model:empero-ai/qwen3.8-9... Base model:jackrong/qwopus3.5-... Base model:merge:empero-ai/qwe... Base model:merge:jackrong/qwop... Base model:merge:orionllm/oxco... Base model:merge:ornith-ai/orn... Base model:merge:qwen/qwen3.5-... Base model:merge:xiaomimimo/mi... Base model:orionllm/oxcoder-9b Base model:ornith-ai/ornith-1.... Base model:qwen/qwen3.5-9b Base model:xiaomimimo/mimo-v2.... Code Conversational Della Deltanet En Endpoints compatible Geodella Linear-attention Merge Model-stock Qwen Qwen3.5 Qwen3 5 text Reasoning Region:us Safetensors Sharded Swe-bench Tensorflow Ties Zh

Model Card on HF 🤗: https://huggingface.co/pragmaticcs/PentaCoder-9B

PentaCoder 9B Parameters and Internals

LLM Name	PentaCoder 9B
Repository 🤗	https://huggingface.co/pragmaticcs/PentaCoder-9B
Base Model(s)	Qwen/Qwen3.5-9B XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B ornith-ai/Ornith-1.5-9B Jackrong/Qwopus3.5-9B-Coder OxCoder 9B empero-ai/Qwen3.8-9B-Distill Qwen/Qwen3.5-9B XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B ornith-ai/Ornith-1.5-9B Jackrong/Qwopus3.5-9B-Coder OrionLLM/OxCoder-9B empero-ai/Qwen3.8-9B-Distill
Model Size	9b
Required VRAM	17.9 GB
Updated	2026-09-30
Maintainer	pragmaticcs
Model Type	qwen3_5_text
Model Files	4.7 GB: 1-of-4 4.8 GB: 2-of-4 4.7 GB: 3-of-4 3.7 GB: 4-of-4
Supported Languages	en zh
Model Architecture	Qwen3_5ForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Transformers Version	5.12.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	248320
Torch Data Type	bfloat16
Errors	replace

Rank the PentaCoder 9B 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 PentaCoder 9B

Best Alternatives	Context / RAM	Downloads	Likes
...thos 9B V2 Heretic Abliterated	1024K / 17.9 GB	80	3
Le Gros Chaton	256K / 17.9 GB	235	1
NeoHorse 1 9B	256K / 18 GB	1250	196
JEV 9B	256K / 17.8 GB	471	12
WikiQwen 9B	256K / 17.9 GB	1039	0
JevK5 9B	256K / 17.9 GB	683	1
...te Qwopus MiMo Ornith 9B Coder	256K / 17.8 GB	251	4
ViAble 1.7 9B	256K / 17.9 GB	1118	3
FlashModel Qwen3.5 9B	256K / 17.9 GB	325	0
Estragon 9B	256K / 17.9 GB	518	0

Note: green Score (e.g. "73.2") means that the model is better than pragmaticcs/PentaCoder-9B.