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mlx-community/SenseNova-U1.5-8B-MoT-8step-4bit
SenseNova-U1.5-8B-MoT-8step-4bit is a any-to-any model from mlx-community. Use it for the any-to-any task on the model card, and read the license before you ship it in a product. It is set up for mlx. The card lists the license as apache-2.0.
Apple Silicon (MLX) artifact of SenseNova-U1.5-8B-MoT — SenseTime's unified T2I + editing + VQA flagship (NEO-unify Mixture-of-Transformers, pixel-space rectified flow, no VAE).
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How the weights are stored.
U3216.2B · 92%
From the Hugging Face model README
Apple Silicon (MLX) artifact of SenseNova-U1.5-8B-MoT — SenseTime's unified T2I + editing + VQA flagship (NEO-unify Mixture-of-Transformers, pixel-space rectified flow, no VAE).
This artifact is the official 8-step distillation LoRA (merged as above) plus 4-bit (group 64) stream quantization.
Quantization: group size 64, 4-bit (mlx convention quantization block in config.json).
Runtime: sensenova-u1-swift (MLX-Swift). Weights are stored in the runtime's key layout (NHWC convs; quantized linears as weight/scales/biases) and load with zero conversion transient — peak load memory ≈ resident.
peak 14.8 GB · 1024² in 3.2 s · 2048² in 15.8 s
Use it for: the smallest, fastest tier for T2I and editing — fits 16 GB-class Macs. Note: 4-bit weight quantization on a diffusion path measurably perturbs the denoise trajectory: at a fixed seed it produces a different but equally valid image (cos ~0.92 vs bf16). Prefer the 8-bit tier when bf16-faithful output matters.
Editing and VQA run on this tier too (runtime ≥ 0.5.1, 2026-10-11): the distill adapter touches only the 294 generation-stream projections, so VQA uses the base tier's understanding stream unchanged (answers match token for token), and the 8-step cfg-free edit matches the 50-step base edit (a 2048² jacket edit in 15 s vs 169 s, 28.7 dB apart). Think mode stays a base-tier feature. Evidence: Docs/receipts/8step-v2-ab/ and AB-R-0490 in the runtime repo.
git clone https://github.com/xocialize/sensenova-u1-swift && cd sensenova-u1-swift && swift build -c release
hf download mlx-community/SenseNova-U1.5-8B-MoT-8step-4bit --local-dir SenseNova-U1.5-8B-MoT-8step-4bit
.build/release/sensenova-cli --weights SenseNova-U1.5-8B-MoT-8step-4bit \
--prompt "A cinematic mountain lake at sunrise, realistic photography." \
--width 1024 --height 1024 --steps 8 --cfg 1.0 --out out.npy
The runtime also does instruction editing (--edit-image) and VQA (--vqa) on this tier, and <think> reasoning mode (--think) on the base tiers — see the repository README for the full surface and the parity report (component parity < 1e-4; e2e per-pass cosine 0.999+ vs the reference PyTorch implementation).
07d76f6, Apache-2.0, by SenseTime / SenseNova — paper · reference implementation.tokenizer.json is generated from the upstream vocab.json/merges.txt (byte-identical tokenization, verified against reference ids).