# Arcee Trinity Large

Hacker Approved page: https://hackerapproved.com/p/trinity-large/

12 people recommended Arcee Trinity Large in Hacker News comments, 4 had mixed feelings and 5 criticized it, November 2025 to October 2026. It was recommended in 4 of 12 months, in 4 threads. It does not meet the Hacker Approved badge rule.

8 of the 12 people who recommend it commented in one thread, “Trinity Large: American Open Source Foundation Model”.

**Verdict:** Praised as a rare fully open-weights American model with strong value; critics say it is undertrained and weak on agentic tasks.

Summary written by Claude from 22 comments.

## Why people recommend it

- Open-weight model from the US (3 comments in the sample): "So refreshing to see open source models like this come from the US" ([source](https://news.ycombinator.com/item?id=46803092)) "one of the first high-performing fully open weight American models" ([source](https://news.ycombinator.com/item?id=47609460)) "Trinity Large is American and quite decent" ([source](https://news.ycombinator.com/item?id=48927979))
- Low cost for its performance (2 comments in the sample): "done something with $20m that is so good people think it must have been a $100m" ([source](https://news.ycombinator.com/item?id=46813803)) "That's crazy affordable. Promising!" ([source](https://news.ycombinator.com/item?id=47609358))
- Promising, impressive results overall (2 comments in the sample): "the model is coming close to QWEN and Deepseek. Pretty impressive" ([source](https://news.ycombinator.com/item?id=46792419)) "This is a wonderful release." ([source](https://news.ycombinator.com/item?id=46798305))

## What people warn about

- Undertrained and not fully post-trained (3 comments in the sample): "It's just undertrained and undersized (in terms of active parameters" ([source](https://news.ycombinator.com/item?id=46804744)) "Its still not fully post trained and its a non-reasoning model, but its worth keeping an eye on" ([source](https://news.ycombinator.com/item?id=47113261)) "The models need another couple point releases worth of post-training to make useful agents" ([source](https://news.ycombinator.com/item?id=48928644))
- Weak at agentic tasks (2 comments in the sample): "it was pretty dumb: it failed to understand the order of jobs in a Github Action" ([source](https://news.ycombinator.com/item?id=46811506)) "Trinity Large Preview managed 17/25 on my agentic SQL benchmark" ([source](https://news.ycombinator.com/item?id=47609634))
- Trails newer rival models (1 comment in the sample): "but GLM's at 5.1 now. I hope they catch up." ([source](https://news.ycombinator.com/item?id=47609602))

## Other open-weight language models people recommend

- [Qwen 3.8 27B](https://hackerapproved.com/p/qwen-3-8-27b/): 804 recommend, 242 mixed, 301 criticize
- [Z.ai GLM](https://hackerapproved.com/p/glm-5-2/): 750 recommend, 181 mixed, 278 criticize
- [Kimi](https://hackerapproved.com/p/kimi-k3/): 652 recommend, 182 mixed, 275 criticize
- [Gemma 4](https://hackerapproved.com/p/gemma-4/): 524 recommend, 120 mixed, 166 criticize

## The badge

A product earns the Hacker Approved badge when at least 10 people recommend it, recommenders outnumber critics at least 2 to 1 (mixed feelings count toward neither side), it was recommended in at least 4 of the 12 months and in at least 5 different threads, and no single thread supplies more than half of the people who recommend it. Health and money products are never badged.

## Cite as

Hacker Approved, "Arcee Trinity Large", https://hackerapproved.com/p/trinity-large/ (12 recommend, 4 mixed, 5 criticize; Hacker News comments, November 2025 to October 2026).

Counts updated 2 Nov 2026, with data through October 31, 2026.