arcee-ai / Trinity-Large-Preview-GGUF

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Total runs: 1.5K
24-hour runs: 0
7-day runs: 130
30-day runs: 1.5K
Model's Last Updated: January 29 2026

Introduction of Trinity-Large-Preview-GGUF

Model Details of Trinity-Large-Preview-GGUF

Arcee Trinity Large

Trinity-Large-Preview-GGUF

Introduction

Trinity-Large-Preview is a 398B-parameter sparse Mixture-of-Experts (MoE) model with approximately 13B active parameters per token. It is the largest model in Arcee AI's Trinity family, trained on more than 17 trillion tokens and delivering frontier-level performance with strong long-context comprehension. Trinity-Large-Preview is a lightly post-trained model based on Trinity-Large-Base.

This repository contains the GGUF quantized weights of Trinity-Large-Preview.

Try it at chat.arcee.ai

More details on the training of Trinity Large are available in the technical report .

Model Variants

The Trinity Large family consists of three checkpoints from the same training run:

Architecture

Trinity-Large-Preview uses a sparse MoE configuration designed to maximize efficiency while maintaining large-scale capacity.

Hyperparameter Value
Total parameters ~398B
Active parameters per token ~13B
Experts 256 (1 shared)
Active experts 4
Routing strategy 4-of-256 (1.56% sparsity)
Dense layers 6
Pretraining context length 8,192
Context length after extension 512k
Architecture Sparse MoE (AfmoeForCausalLM)
Benchmarks
Benchmark Llama 4 Maverick Trinity-Large Preview
MMLU 85.5 87.2
MMLU-Pro 80.5 75.2
GPQA-Diamond 69.8 63.3
AIME 2025 19.3 24.0
Training Configuration
Pretraining
  • Training tokens: 17 trillion
  • Data partner: Datology
Powered by Datology
Posttraining
  • This checkpoint was instruction tuned on 20B tokens.
Infrastructure
  • Hardware: 2,048 NVIDIA B300 GPUs
  • Parallelism: HSDP + Expert Parallelism
  • Compute partner: Prime Intellect
Powered by Prime Intellect
Usage
Running our model
llama.cpp

Supported in llama.cpp release b7061+

llama-server -hf arcee-ai/Trinity-Large-Preview-GGUF:q4_k_m
LM Studio

Supported in the latest LM Studio runtime. Search for arcee-ai/Trinity-Large-Preview-GGUF in Model Search.

API

Available on OpenRouter:

curl -X POST "https://openrouter.ai/v1/chat/completions" \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "arcee-ai/trinity-large-preview",
    "messages": [
      {
        "role": "user",
        "content": "What are some fun things to do in New York?"
      }
    ]
  }'
License

Trinity-Large-Preview is released under the Apache License, Version 2.0.

Citation
@misc{arcee_trinity_large_preview,
  title = {Trinity-Large-Preview},
  author = {{Arcee AI}},
  year = {2026},
  note = {398B sparse MoE model trained on 17T tokens}
}

Runs of arcee-ai Trinity-Large-Preview-GGUF on huggingface.co

1.5K
Total runs
0
24-hour runs
18
3-day runs
130
7-day runs
1.5K
30-day runs

More Information About Trinity-Large-Preview-GGUF huggingface.co Model

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Trinity-Large-Preview-GGUF huggingface.co is an AI model on huggingface.co that provides Trinity-Large-Preview-GGUF's model effect (), which can be used instantly with this arcee-ai Trinity-Large-Preview-GGUF model. huggingface.co supports a free trial of the Trinity-Large-Preview-GGUF model, and also provides paid use of the Trinity-Large-Preview-GGUF. Support call Trinity-Large-Preview-GGUF model through api, including Node.js, Python, http.

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Trinity-Large-Preview-GGUF install

Trinity-Large-Preview-GGUF is an open source model from GitHub that offers a free installation service, and any user can find Trinity-Large-Preview-GGUF on GitHub to install. At the same time, huggingface.co provides the effect of Trinity-Large-Preview-GGUF install, users can directly use Trinity-Large-Preview-GGUF installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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