What are the hardware requirements for Trinity Mini Base Pre Anneal?

Trinity Mini Base Pre Anneal requires approximately 52.3 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Trinity Mini Base Pre Anneal and how large is it?

Trinity Mini Base Pre Anneal is developed by arcee-ai, a model with 26.1b 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 Trinity Mini Base Pre Anneal?

Trinity Mini Base Pre Anneal is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Trinity Mini Base Pre Anneal by arcee-ai — VRAM 52.3GB, 4K context

Name: Trinity Mini Base Pre Anneal
Author: arcee-ai

Trinity Mini Base Pre Anneal is an open-source language model by arcee-ai. Features: 26.1b LLM, VRAM: 52.3GB, Context: 4K, License: other, LLM Explorer Score: 0.22.

Afmoe Ar Custom code De En Endpoints compatible Es Fr Hi It Ko Pt Region:us Ru Safetensors Sharded Tensorflow Zh

Model Card on HF 🤗: https://huggingface.co/arcee-ai/Trinity-Mini-Base-Pre-Anneal

Trinity Mini Base Pre Anneal Parameters and Internals

LLM Name	Trinity Mini Base Pre Anneal
Repository 🤗	https://huggingface.co/arcee-ai/Trinity-Mini-Base-Pre-Anneal
Model Size	26.1b
Required VRAM	52.3 GB
Updated	2026-08-06
Maintainer	arcee-ai
Model Type	afmoe
Model Files	2.0 GB: 1-of-27 2.0 GB: 2-of-27 2.0 GB: 3-of-27 2.0 GB: 4-of-27 2.0 GB: 5-of-27 2.0 GB: 6-of-27 2.0 GB: 7-of-27 2.0 GB: 8-of-27 2.0 GB: 9-of-27 2.0 GB: 10-of-27 2.0 GB: 11-of-27 2.0 GB: 12-of-27 2.0 GB: 13-of-27 2.0 GB: 14-of-27 2.0 GB: 15-of-27 2.0 GB: 16-of-27 2.0 GB: 17-of-27 2.0 GB: 18-of-27 2.0 GB: 19-of-27 2.0 GB: 20-of-27 2.0 GB: 21-of-27 2.0 GB: 22-of-27 2.0 GB: 23-of-27 2.0 GB: 24-of-27 2.0 GB: 25-of-27 1.5 GB: 26-of-27 0.8 GB: 27-of-27
Supported Languages	en es fr de it pt ru ar hi ko zh
Model Architecture	AfmoeForCausalLM
License	other
Context Length	4096
Model Max Length	4096
Transformers Version	4.57.1
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|pad\|>
Vocabulary Size	200192

Rank the Trinity Mini Base Pre Anneal 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 Trinity Mini Base Pre Anneal

Best Alternatives	Context / RAM	Downloads	Likes
Trinity Mini	128K / 52.3 GB	25533	198
Trinity Mini Base	128K / 52.3 GB	2331	22
Trinity Mini FP8 Block	128K / 27.8 GB	237	2

Note: green Score (e.g. "73.2") means that the model is better than arcee-ai/Trinity-Mini-Base-Pre-Anneal.