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soundTeam/Q3-30B-A3B-Designant_mlx-8bpw
Q3-30B-A3B-Designant_mlx-8bpw is a text generation model from soundTeam. Use it when you need the model to write or continue text. It is set up for transformers.
<img src="https://cdn-uploads.huggingface.co/production/uploads/6685d39f64da708c0f553c5d/1yVqoNrokaI2JbrjcCk1W.png" title="Made with NovelAI 4.5 Curated" width="750" height="750"</img
Downloads · 30 days
11
10% of all-time downloads
All-time downloads
109
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8.6B
32.5 GB on disk
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.safetensors32.4 GB · 100%
How the weights are stored.
U327.6B · 89%
From the Hugging Face model README
<img src="https://cdn-uploads.huggingface.co/production/uploads/6685d39f64da708c0f553c5d/1yVqoNrokaI2JbrjcCk1W.png" title="Made with NovelAI 4.5 Curated" width="750" height="750"></img>
She looked into His Spine, into His Heart; and she saw there the shade of His soul.
Intended as a direct upgrade to Pentiment, Q3-30B-A3B-Designant is a roleplaying model finetuned from Qwen3-30B-A3B-Base.
During testing, Designant punched well above its weight class in terms of active parameters, demonstrating the potential for well-made lightweight Mixture of Experts models in the roleplay scene. While one tester observed looping behavior, repetition in general was minimal.
Coming Soon™ from allura-quants and your favourite quant accounts.
Format is plain-old ChatML (please note that, unlike regular Qwen 3, you do not need to prefill empty think tags for it not to reason -- see below).
Settings used by testers varied, but Fizz and inflatebot used the same settings and system prompt recommended for GLM4-32B-Neon-v2.
The instruction following version of Qwen3-30B-A3B was not part of the merge. Instruction-following is trained in post-hoc, and "thinking" data was not included. As a result of this, "thinking" will likely not function as intended.
As with any Q3-30B-A3B, Designant performs very adequately with few or zero layers offloaded to GPU. When using the ik_llama.cpp server, a 7950X CPU with 32GB of DDR5 RAM can run a Q4_K_M quant of this architecture at ~15 tokens/sec with no GPU involved at all.
The base model first went through a supervised finetune on a corpus of instruction following data, roleplay conversations, and human writing based on the Ink/Bigger Body/Remnant lineage.
It was then slightly merged with Pantheon-Proto-RP-1.8, to improve stability.
Finally, a KTO reinforcement learning phase steered the model away from the very purple prose the initial merge had, and improved its logical+spatial reasoning and sense of overall "intelligence".
Fizz - Train, Merge, Data Wrangling
Toaster, OMGWTFBBQ, The Trashpanda Testing Crew - Testing
inflatebot - Model Card, Testing, Merging Consultation
Juahyori, Artus - Compute Funding
Gryphe, Alibaba - Making the original models as well as the ones used in the merge
Bot would like to thank the Allura community on Discord, especially Curse, Vagabond, Artus and Mawnipulator, for their companionship and moral support. You all mean the world to us.
<sup>There, God is not.</sup>