Instructions to use MLXBits/ltx-2.3-10eros-v1.3-dmd-mlx-q8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use MLXBits/ltx-2.3-10eros-v1.3-dmd-mlx-q8 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir ltx-2.3-10eros-v1.3-dmd-mlx-q8 MLXBits/ltx-2.3-10eros-v1.3-dmd-mlx-q8
- LTX.io
How to use MLXBits/ltx-2.3-10eros-v1.3-dmd-mlx-q8 with LTX.io:
# Install the LTX-2 pipelines git clone https://github.com/Lightricks/LTX-2.git cd LTX-2 uv sync --frozen
# Download the weights from this repo, plus the Gemma text encoder hf download MLXBits/ltx-2.3-10eros-v1.3-dmd-mlx-q8 --local-dir models/ltx-2.3-10eros-v1.3-dmd-mlx-q8 hf download google/gemma-3-12b-it-qat-q4_0-unquantized --local-dir models/gemma-3-12b
# Fast pipeline (distilled model, no distilled LoRA needed) uv run python -m ltx_pipelines.distilled \ --distilled-checkpoint-path models/ltx-2.3-10eros-v1.3-dmd-mlx-q8/<distilled-checkpoint>.safetensors \ --spatial-upsampler-path models/ltx-2.3-10eros-v1.3-dmd-mlx-q8/<spatial-upsampler>.safetensors \ --gemma-root models/gemma-3-12b \ --prompt "A beautiful sunset over the ocean" \ --output-path output.mp4 # For image-to-video, add: --image path/to/image.jpg 0 0.8# HQ pipeline (two-stage, higher quality) uv run python -m ltx_pipelines.ti2vid_two_stages_hq \ --checkpoint-path models/ltx-2.3-10eros-v1.3-dmd-mlx-q8/<checkpoint>.safetensors \ --distilled-lora models/ltx-2.3-10eros-v1.3-dmd-mlx-q8/<distilled-lora>.safetensors 0.8 \ --spatial-upsampler-path models/ltx-2.3-10eros-v1.3-dmd-mlx-q8/<spatial-upsampler>.safetensors \ --gemma-root models/gemma-3-12b \ --prompt "A beautiful sunset over the ocean" \ --output-path output.mp4 # For image-to-video, add: --image path/to/image.jpg 0 0.8 - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
LTX-2.3 10Eros v1.3 DMD β MLX int8 (q8)
Int8 (8-bit) MLX quantization of TenStrip/LTX2.3-10Eros v1.3 with the JoyAI Echo DMD distillation baked directly into the transformer, replacing the native rank-384 distilled LoRA.
Converted with mlx-forge and packaged for ltx-2-mlx β a pure-MLX port of LTX-2 for Apple Silicon.
Not for all audiences. 10Eros is intended for adult use. By downloading and running this model you confirm you are of legal age in your jurisdiction and accept responsibility for the content you generate. Do not use it to produce illegal material or to depict real, identifiable people without consent.
What this is
This is a distilled-only package. The DMD distillation deltas extracted from JoyAI Echo (rank-256, reshaped from the LTX 384 1.1 distilled-LoRA shapes, audio branch sourced from the 384 1.1 distilled LoRA) were merged into the 10Eros v1.3 base at strength 1.0, producing a standalone distilled transformer. There is no dev transformer and no runtime LoRA fusion β the distillation is already in the weights.
Compared to the native 384 distilled LoRA, the DMD merge avoids the resampling-to-base drift, the conditioning drop from the latent, and the extra detail/look overwrites that the stock distilled LoRA introduces at the upscale refine stage.
Run it with --distilled. The two-stage (--two-stage, --two-stages-hq) and one-stage-dev (--one-stage) paths are not available here β they require a dev transformer, which this package intentionally omits.
What's in here
| File | Size | Role |
|---|---|---|
transformer-distilled-1.1.safetensors |
~19.2 GB | Distilled transformer with the JoyAI Echo DMD deltas pre-fused, int8 |
connector.safetensors |
~5.9 GB | Gemma β DiT embedding connectors |
spatial_upscaler_x1_5_v1_0.safetensors |
~1.0 GB | 1.5Γ neural latent upscaler |
spatial_upscaler_x2_v1_1.safetensors |
~950 MB | 2Γ neural latent upscaler (stage-2 refine) |
vae_encoder.safetensors / vae_decoder.safetensors |
~1.4 GB | Video VAE (8Γ temporal, 32Γ spatial) |
temporal_upscaler_x2_v1_0.safetensors |
~250 MB | 2Γ temporal upscaler |
vocoder.safetensors |
~250 MB | BigVGAN v2 vocoder + BWE generator |
audio_vae.safetensors |
~106 MB | Audio VAE decoder |
Quantization: int8, group size 64, applied only to nn.Linear inside transformer_blocks. AdaLN, projections, connectors, VAE and vocoder remain bf16 (MLX cannot quantize Conv layers).
Text encoder: Gemma 3 12B is not bundled β ltx-2-mlx loads it separately via mlx-lm.
mlx-forge may also drop
ltx-2.3-22b-distilled-lora-384*.safetensors(~7.1 GB each) into this directory as "shared" LoRA components. They are unused in a distilled-only package β nothing fuses them (there is no dev transformer, and--distillednever loads a LoRA). Safe to delete; also remove them from theloralist insplit_model.json.
Usage
Requires ltx-2-mlx on Apple Silicon.
# Text-to-video (distilled two-stage: half-res β upscale β full-res refine)
ltx-2-mlx generate \
--model /path/to/ltx-2.3-10eros-v1.3-dmd-mlx-q8 \
--prompt "your prompt" \
--distilled \
-H 480 -W 704 -f 97 -o out.mp4
# Image-to-video β add --image
ltx-2-mlx generate \
--model /path/to/ltx-2.3-10eros-v1.3-dmd-mlx-q8 \
--prompt "animate this" \
--distilled --image photo.jpg -o out.mp4
Default distilled flow is the usual 8/4-step upscale schedule. Experiment with other sigmas or any Euler / LTX-compatible sampler β no custom loading or sampling is needed. On 32 GB Macs add --low-ram for block-streamed inference; q8 fits 16 GB with --low-ram.
Conversion provenance
The JoyAI Echo DMD LoRA was merged into the 10Eros v1.3 bf16 base at per-layer strength 1.0 (alpha Γ· actual rank) to produce a distilled bf16 checkpoint:
uv run ~/mlx-forge/scripts/merge_lora.py # LoRA: LTX2.3_DMD_reshaped_r256.safetensors # β /Volumes/Storage/10Eros-v1.3-distilled-dmd-bf16.safetensorsDistilled variant + all shared components + upscalers, quantized to int8:
uv run mlx-forge convert ltx-2.3 --variant distilled-1.1 \ --checkpoint /Volumes/Storage/10Eros-v1.3-distilled-dmd-bf16.safetensors \ --quantize --bits 8 \ --spatial-upscaler x2 x1.5 --temporal-upscaler x2 \ --output models/ltx-2.3-10eros-v1.3-dmd-mlx-q8
No dev variant is added β this package is distilled-only by design.
Credits & license
- DMD distillation: JoyAI Echo β 10S-Comfy-nodes
- Finetune: TenStrip/LTX2.3-10Eros
- Base model: Lightricks/LTX-2.3
- Conversion: mlx-forge Β· Runtime: ltx-2-mlx
Distributed under the LTX-2 license. The 10Eros finetune's own terms also apply β review the upstream model card before redistribution.
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Model tree for MLXBits/ltx-2.3-10eros-v1.3-dmd-mlx-q8
Base model
TenStrip/LTX2.3-10Eros