Trinity-Large-Thinking
Release in the Trinity family · version Large-Thinking
Trinity-Large-Thinking is a reasoning-tuned sparse mixture-of-experts model with about 398B total and 13B active parameters per token and a 512k-token context window. It was post-trained from Trinity-Large-Base with chain-of-thought and agentic reinforcement learning, and writes its reasoning in think blocks before answering.1
- Model hub: Model card (external site: huggingface.co)
- License: License (OpenMDW-1.1) (external site: huggingface.co)
- Release notes: Release announcement (external site: arcee.ai)
- Paper: Technical report (external site: arxiv.org)
Availability and license
Overall availability
Weights download from Hugging Face without an access gate. Also served through Arcee's paid API and OpenRouter.16
Availability is separate from permission: read the license before using or redistributing.
Arcee announced this release on 2026-04-01 under Apache 2.0. On 2026-05-28 the Hugging Face repository changed its license to OpenMDW-1.1, and Arcee states it moved earlier Trinity releases to that license. OpenMDW-1.1 grants broad use rights and places no restrictions on outputs. It requires keeping the license and notices when redistributing, and ends the rights of anyone who sues claiming the materials infringe a patent or copyright.6372
Model-disclosure tier
The model parameters for this release can be downloaded by the public. License terms may still restrict use, redistribution, or commercial use.
The weights are under a license that is not on the rubric's OSI-approved list. Read its terms before use.
Public materials checklist
| Item | Status | Notes and evidence |
|---|---|---|
| WeightsCan the general public download the model parameters for this release? | Public | Weights are in the ungated Hugging Face repository; Arcee also publishes GGUF, FP8, NVFP4, and W4A16 variants as separate repositories.15 |
| Inference codeIs code for running the model published? | Public | The repository includes modeling code (modeling_afmoe.py), and the model card documents running it with vLLM and Transformers.14 |
| Training codeIs the code used to train the model published? | Unknown | The technical report says training used a modified version of TorchTitan but does not link a release.9 |
| Training-data informationPublic = the training data itself can be obtained. Partial = composition or sources are documented without full access. | Partial | The technical report describes the pretraining mix (curated web, synthetic, multilingual, and code data). No public release of the data itself was found.9 |
| Training recipeAre the training configuration and procedure documented in enough detail to follow? | Partial | Pretraining settings are documented in the technical report. The post-training for this variant is described only briefly on the model card.91 |
| Evaluation materialsPublic = evaluation code or prompts that let others re-run the evaluations are published. Partial = results only. | Partial | Benchmark results are published on the model card; evaluation code is not linked.1 |
What it is useful for
The model card documents it for tool calling, multi-step planning, and use as the model behind agent frameworks, and notes that reasoning content must be kept in the conversation history across turns.1
Run and use notes
- The model card documents serving with vLLM 0.11.1 or later, using the deepseek_r1 reasoning parser and qwen3_coder tool-call parser, and running with Transformers from the main branch or with trust_remote_code enabled.1
Organization context
Provenance and derivatives
Post-trained from Trinity-Large-Base, Arcee's own 17-trillion-token pretrained checkpoint. The model card names Datology as data partner and Prime Intellect as compute partner.1
- Derived from: Trinity-Large-Base (external site: huggingface.co) — Same organization; pretrained foundation checkpoint.
Other releases in the Trinity family
- Trinity MiniModel-disclosure tier (USASI rubric v0.1): Open-weight
U.S. eligibility
Sources
This listing is not an endorsement, a safety assessment, or a federal approval.