The published Core ML conversions of sd-turbo are compiled for Mac GPU (ORIGINAL attention), shipped uncompressed (fp16, ~2.5 GB), and locked to resolutions we could not use. Those three properties are baked in at conversion time and cannot be changed at runtime.

This conversion targets the opposite end: a phone. It trades away flexibility — one fixed resolution, no guidance, no img2img — for a bundle that fits in memory on a 4 GB iPhone and runs on the Neural Engine.

Conversion parameters

Every value below is compiled in and cannot be changed at runtime.

Parameter	Value	Why
Resolution	384 × 384 (latent 48 × 48)	512 renders subjects too small; 256 crops too tightly
Attention	`SPLIT_EINSUM` (v1)	Targets the Neural Engine. `SPLIT_EINSUM_V2` requires the latent width to be a multiple of 512, so it cannot do 384
Quantization	6-bit palettized (text encoder + U-Net)	VAE decoder left at fp16 — it is small and quality-sensitive
U-Net batch size	1	sd-turbo does not use classifier-free guidance; batch 2 doubles the work for nothing (measured: 2.07× faster at batch 1)
VAE encoder	not included	Text-to-image only
Compute units	`CPU_AND_NE`

Produced with apple/ml-stable-diffusion:

python -m python_coreml_stable_diffusion.torch2coreml \
  --model-version stabilityai/sd-turbo \
  --convert-unet --convert-text-encoder --convert-vae-decoder \
  --attention-implementation SPLIT_EINSUM \
  --quantize-nbits 6 \
  --latent-h 48 --latent-w 48 \
  --unet-batch-one \
  --bundle-resources-for-swift-cli \
  --compute-unit CPU_AND_NE

Runtime settings

These are not compiled in, but the bundle only behaves correctly with them:

Setting	Value
Scheduler	LCM (see the caveat below)
Steps	4
Guidance scale	0.0
Compute units	`cpuAndNeuralEngine`
`reduceMemory`	`true` on iPhone

⚠️ Upstream apple/ml-stable-diffusion has no LCM scheduler

LCM support has been open and unmerged since 2024 (apple/ml-stable-diffusion#319). To use this model you need LCMScheduler.swift, which exists in keijiro's fork. Cherry-picking the single commit bd0cb9e onto current apple/main is enough — it is ~180 lines, and the three conflicts are each one extra case in a switch.

17 files, 1,072,200,142 bytes (~1.07 GB) total.

├── manifest.json                     ← integrity + version metadata
├── TextEncoder.mlmodelc/             304 MB
├── Unet.mlmodelc/                    620 MB
├── VAEDecoder.mlmodelc/               94 MB
├── vocab.json
└── merges.txt

.mlmodelc entries are directories, not files. They are stored here unarchived so that a client can stream them file-by-file and reconstruct the tree, rather than downloading a ~1 GB archive and needing ~2 GB of free space to unpack it.

`manifest.json`

json

{
  "schemaVersion": 1,
  "modelVersion": "1.0.0",
  "totalBytes": 1072200142,
  "files": [
    { "path": "Unet.mlmodelc/weights/weight.bin", "bytes": 650117120, "sha256": "..." }
  ]
}

Fetch this small file first to get the download size up front, verify each file with its SHA-256 as it lands, and detect when a newer modelVersion is published. Files are served at:

https://huggingface.co/jivenchy/sd-turbo-coreml-384-6bit/resolve/main/<path>

License

Full text: LICENSE.md
Attribution and the complete list of modifications: NOTICE

Your own use of this model is governed by that license. Two provisions are easy to miss:

Commercial use requires registration with Stability AI at https://stability.ai/community-license.
The license terminates if you or your affiliates generate more than USD $1,000,000 in annual revenue; an enterprise license is then required (https://stability.ai/enterprise).

Use is also subject to the Stability AI Acceptable Use Policy.

This is an unofficial community conversion. It is not affiliated with, endorsed by, or supported by Stability AI or Apple.

jivenchy/
sd-turbo-coreml-384-6bit

sd-turbo — Core ML, 384×384, 6-bit (Apple Neural Engine)

Why this exists

Conversion parameters

Runtime settings

⚠️ Upstream `apple/ml-stable-diffusion` has no LCM scheduler

Contents

`manifest.json`

License

jivenchy/sd-turbo-coreml-384-6bit

sd-turbo — Core ML, 384×384, 6-bit (Apple Neural Engine)

Why this exists

Conversion parameters

Runtime settings

⚠️ Upstream apple/ml-stable-diffusion has no LCM scheduler

Contents

manifest.json

License

jivenchy/
sd-turbo-coreml-384-6bit

⚠️ Upstream `apple/ml-stable-diffusion` has no LCM scheduler

`manifest.json`