What are the hardware requirements for Triumvirate Qwopus MiMo Ornith 9B Coder?

Triumvirate Qwopus MiMo Ornith 9B Coder requires approximately 17.8 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 Triumvirate Qwopus MiMo Ornith 9B Coder and how large is it?

Triumvirate Qwopus MiMo Ornith 9B Coder 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 Triumvirate Qwopus MiMo Ornith 9B Coder?

Triumvirate Qwopus MiMo Ornith 9B Coder is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Triumvirate Qwopus MiMo Ornith 9B Coder by pragmaticcs — VRAM 17.8GB, 256K context

Name: Triumvirate Qwopus MiMo Ornith 9B Coder
Author: pragmaticcs

Triumvirate Qwopus MiMo Ornith 9B Coder is an open-source language model by pragmaticcs. Features: 9b LLM, VRAM: 17.8GB, Context: 256K, License: apache-2.0, LLM Explorer Score: 0.26.

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

Model Card on HF 🤗: https://huggingface.co/pragmaticcs/Triumvirate-Qwopus-MiMo-Ornith-9B-Coder

Triumvirate Qwopus MiMo Ornith 9B Coder Parameters and Internals

LLM Name	Triumvirate Qwopus MiMo Ornith 9B Coder
Repository 🤗	https://huggingface.co/pragmaticcs/Triumvirate-Qwopus-MiMo-Ornith-9B-Coder
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 Qwen/Qwen3.5-9B XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B ornith-ai/Ornith-1.5-9B Jackrong/Qwopus3.5-9B-Coder
Model Size	9b
Required VRAM	17.8 GB
Updated	2026-09-24
Maintainer	pragmaticcs
Model Type	qwen3_5_text
Model Files	2.0 GB: 1-of-6 3.8 GB: 2-of-6 3.7 GB: 3-of-6 3.7 GB: 4-of-6 3.7 GB: 5-of-6 0.9 GB: 6-of-6
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 Triumvirate Qwopus MiMo Ornith 9B Coder 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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...thos 9B V2 Heretic Abliterated	1024K / 17.9 GB	80	3
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Note: green Score (e.g. "73.2") means that the model is better than pragmaticcs/Triumvirate-Qwopus-MiMo-Ornith-9B-Coder.