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Umixer

umixer

Models in Library1
Datasets in Library0
Models on Hugging Face1
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This profile connects the 1 model and dataset record shown below to their upstream cards and sources. The library counts describe SAVRN's coverage, rather than this publisher's entire output.

Published tasks: Text generation.

Reported licenses: other. Open a record to review its specific license and conditions.

Compare model specifications, source dates, and hardware estimates on the individual records. Publisher identity verification is separate from a model's quality, deployment readiness, or suitability for your work.

Models

Model · Text generation

Qwen3.8-Flash-Next-oQ4e-mix6-mtp

Umixer

Goal: oQ4e speed and memory footprint, oQ5e-or-better quality reaching toward oQ6e. Runs at ~73–75 GB resident with ~82→66 tok/s decode on a 128 GB Apple Silicon host — the speed/RAM economics of a 4-bit build, at an accuracy tier equal to or above uniform oQ5e. How: a mixed-precision MLX build of Qwen3.8-Flash-Next, assembled by component-wise byte-copy from Jundot's native oQ quantizations — zero re-quantization in the entire package. Every tensor is byte-identical to its source, so quality is traceable, not re-derived. Uniform-bit quantization pays accuracy where it isn't needed (middle layers) and loses it where it hurts (first/last layers, n-gram table, attention). A Data-Free…

Open weights other 180B parameters 262,144 tokens mlx