What are the hardware requirements for TripleTrouble?

TripleTrouble requires approximately 69.7 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 TripleTrouble and how large is it?

TripleTrouble is developed by OliviaRossi, a model with 35b 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 TripleTrouble?

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

TripleTrouble by OliviaRossi — VRAM 69.7GB, 256K context

Name: TripleTrouble
Author: OliviaRossi

TripleTrouble is an open-source language model by OliviaRossi. Features: 35b LLM, VRAM: 69.7GB, Context: 256K, License: apache-2.0, Code Generating.

Agent Base model:kwaipilot/kat-coder... Base model:merge:kwaipilot/kat... Base model:merge:ornith-ai/orn... Base model:merge:qwen/qwen-age... Base model:ornith-ai/ornith-1.... Base model:qwen/qwen-agentworl... Codegen Coding Conversational En Gated-deltanet Merge Model-soup Moe Qwen Qwen-35b-a3b Qwen3 5 moe Region:us Safetensors Sharded Tensorflow Tool-use World-model Zh

Model Card on HF 🤗: https://huggingface.co/OliviaRossi/TripleTrouble

TripleTrouble Parameters and Internals

LLM Name	TripleTrouble
Repository 🤗	https://huggingface.co/OliviaRossi/TripleTrouble
Model Name	TripleTrouble
Model Creator	OliviaRossi
Base Model(s)	Kwaipilot/KAT-Coder-V2.5-Dev ornith-ai/Ornith-1.5-35B-A3B Qwen AgentWorld 35B A3B Kwaipilot/KAT-Coder-V2.5-Dev ornith-ai/Ornith-1.5-35B-A3B Qwen/Qwen-AgentWorld-35B-A3B
Model Size	35b
Required VRAM	69.7 GB
Updated	2026-09-13
Maintainer	OliviaRossi
Model Type	qwen3_5_moe
Model Files	5.4 GB: 0-of-13 5.4 GB: 1-of-13 5.4 GB: 2-of-13 5.4 GB: 3-of-13 5.4 GB: 4-of-13 5.4 GB: 5-of-13 5.4 GB: 6-of-13 5.4 GB: 7-of-13 5.4 GB: 8-of-13 5.4 GB: 9-of-13 5.4 GB: 10-of-13 5.4 GB: 11-of-13 4.9 GB: 12-of-13
Supported Languages	en zh
Generates Code	Yes
Model Architecture	Qwen3_5MoeForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Transformers Version	4.57.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	248320
Torch Data Type	bfloat16
Errors	replace

Rank the TripleTrouble 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 TripleTrouble

Best Alternatives	Context / RAM	Downloads	Likes
Qwen 35B A3B SignOfFour Coder	256K / 70.6 GB	1722	3
SignOfFour	256K / 70.6 GB	728	1
UltiMerge	256K / 69.3 GB	557	2
DAOS Fusion	256K / 69.3 GB	34	2

Note: green Score (e.g. "73.2") means that the model is better than OliviaRossi/TripleTrouble.