# Arcee AI Trinity Large (400B)

> Arcee's flagship blends several efficiency tricks into a DeepSeek-like coarse MoE design; the AA score shown here refers to the Trinity Large Thinking checkpoint.

| Property | Value |
| --- | --- |
| Lab | Arcee AI (United States) |
| Released | 2026-01-27 |
| Decoder type | Sparse MoE |
| Family | Sparse MoE |
| Scale | 400B total, 13B active (3.3% active) |
| Context window | 512,000 tokens |
| Attention | GQA with gated attention and 3:1 sliding-window/global attention |
| Layer mix | 45 sliding-window + 15 global |
| KV cache / token (bf16) | 240 KiB (High) |
| License | Apache License 2.0 |

**Key detail:** Combines QK-Norm, RoPE+NoPE, sandwich norm, and a coarse-grained MoE.

## Architecture concepts

- [QK-Norm (QK-Norm)](https://llm-atlas-7or.pages.dev/concepts/qk-norm.md): RMSNorm applied to queries and keys before attention to keep logits well-behaved.
- [No Positional Embeddings (NoPE)](https://llm-atlas-7or.pages.dev/concepts/nope.md): Some or all layers drop explicit positional encodings and rely on the causal mask.
- [Grouped-Query Attention (GQA)](https://llm-atlas-7or.pages.dev/concepts/gqa.md): Several query heads share one key/value head, shrinking the KV cache with little quality loss.
- [Sliding Window Attention (SWA)](https://llm-atlas-7or.pages.dev/concepts/swa.md): Some layers only attend to a local window of recent tokens instead of the whole context.
- [Mixture of Experts (MoE)](https://llm-atlas-7or.pages.dev/concepts/moe.md): Many feed-forward experts, but a router sends each token to only a few of them.
- [Gated Attention (Gated attention)](https://llm-atlas-7or.pages.dev/concepts/gated-attention.md): A learned sigmoid gate scales the attention output before it re-enters the residual stream.

## Benchmark (Artificial Analysis Intelligence Index)

- AA Intelligence Index v4.3.2: total 10.8 (General 16.6, Scientific 8.4, Coding 20.6, Agents 0.2)

## Links

- Architecture diagram: https://sebastianraschka.com/llm-architecture-gallery/images/architectures/arcee-ai-trinity-large-400b.webp
- View in article: https://magazine.sebastianraschka.com/p/the-big-llm-architecture-comparison#%C2%A720-arcee-ai-trinity-large
- config.json: https://huggingface.co/arcee-ai/Trinity-Large-Base/blob/main/config.json
- Tech report: https://arxiv.org/pdf/2602.17004
- Source card (source of truth): https://sebastianraschka.com/llm-architecture-gallery/#card-arcee-ai-trinity-large-400b
- Web page: https://llm-atlas-7or.pages.dev/models/arcee-ai-trinity-large-400b/
- JSON: https://llm-atlas-7or.pages.dev/api/models/arcee-ai-trinity-large-400b.json

_Data from Sebastian Raschka's LLM Architecture Gallery (https://sebastianraschka.com/llm-architecture-gallery/). Synced 2026-11-04._