Twitter/X

Arcee_ai is a 398B parameter model with only 13B active parameters due to high…

2026-04-04 · 23:38 UTC ·@alexocheema ·0 min read

Brief

Arcee_ai should run well on Apple Silicon RDMA clusters using exolabs because its sparsity reduces active parameters: a 398B model with 13B active parameters, natively 16-bit at ≈800 GB which needs four 256 GB Mac Studios for full precision, or can be quantized to 6-bit to fit on a 128 GB MBP plus a 256 GB Mac Studio (tweeted 2026-04-04).

Why it matters

Arcee_ai is a 398B parameter model with only 13B active parameters due to high sparsity, and is natively 16-bit at ~800 GB—running the full model requires 4 × 256 GB Mac Studios on Apple Silicon RDMA clusters with exolabs.

Key details

  • You can run Arcee_ai quantized to 6-bit across a 128 GB MacBook Pro plus a 256 GB Mac Studio; the tweet (2026-04-04) responds to @beffjezos asking about running Trinity-Large-Thinking.
Source evidence

title: @alexocheema: Yes, @arcee_ai should run well on Apple Silicon RDMA clusters with @exolabs.

It’s a 398B model, 13B...
author: @alexocheema
contenttype: tweet
publication: Twitter/X
published: 2026-04-04T23:38:26+00:00
sourceurl: https://x.com/alexocheema/status/2040574746933305589

word_count: 79

Yes, @arcee_ai should run well on Apple Silicon RDMA clusters with @exolabs.

It’s a 398B model, 13B active parameters (very sparse so great for Apple Silicon).

It’s natively 16-bit at ~800GB so you’d need 4 x 256GB Mac Studios to run the full model.

You can run it in 6-bit on 128GB MBP + 256GB Mac Studio.

Beff (e/acc) (@beffjezos)

Ayo @exolabs can I run a @arcee_ai Trinity-Large-Thinking on a 128GB MBP and a 256GB Mac Studio?

— https://nitter.net/beffjezos/status/2040564261206810682#m