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MLXBits/ltx-2.3-10eros-v1.2-mlx-q8
ltx-2.3-10eros-v1.2-mlx-q8 is a image-text-to-video model from MLXBits. Use it for the image-text-to-video 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 other.
Int8 (8-bit) MLX quantization of TenStrip/LTX2.3-10Eros v1.2.
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From the Hugging Face model README
Int8 (8-bit) MLX quantization of TenStrip/LTX2.3-10Eros v1.2.
Converted with mlx-forge and packaged for ltx-2-mlx — a pure-MLX port of LTX-2 for Apple Silicon.
[!WARNING] 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.
This repo ships the full split layout that ltx-2-mlx expects — both transformer variants plus all shared components, so two-stage, distilled, I2V and audio pipelines all work out of the box.
| File | Size | Role |
|---|---|---|
transformer-dev.safetensors | ~19 GB | Dev transformer (10Eros v1.2 base), int8 |
transformer-distilled-1.1.safetensors | ~19 GB | Distilled transformer with the rank-384 distilled LoRA pre-fused, int8 |
connector.safetensors | ~5.9 GB | Gemma → DiT embedding connectors |
vae_encoder.safetensors / vae_decoder.safetensors | ~1.4 GB | Video VAE (8× temporal, 32× spatial) |
audio_vae.safetensors | ~106 MB | Audio VAE decoder |
vocoder.safetensors | ~250 MB | BigVGAN v2 vocoder + BWE generator |
spatial_upscaler_x2_v1_1.safetensors | ~950 MB | 2× neural latent upscaler |
spatial_upscaler_x1_5_v1_0.safetensors | ~1.0 GB | 1.5× neural latent upscaler |
temporal_upscaler_x2_v1_0.safetensors | ~250 MB | 2× temporal upscaler |
ltx-2.3-22b-distilled-lora-384*.safetensors | ~7.1 GB ea. | Official rank-384 distilled LoRAs (bf16, for the streaming dev→distilled swap path) |
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 — ltx-2-mlx loads it separately via mlx-lm.
Requires ltx-2-mlx on Apple Silicon.
# Text-to-video (distilled, fastest)
ltx-2-mlx generate \
--model /path/to/ltx-2.3-10eros-v1.2-mlx-q8 \
--prompt "your prompt" \
--distilled \
-H 480 -W 704 -f 97 -o out.mp4
# Two-stage (dev + CFG + upscale, recommended quality)
ltx-2-mlx generate \
--model /path/to/ltx-2.3-10eros-v1.2-mlx-q8 \
--prompt "your prompt" \
--two-stage -o out.mp4
# Image-to-video — add --image to any mode
ltx-2-mlx generate \
--model /path/to/ltx-2.3-10eros-v1.2-mlx-q8 \
--prompt "animate this" \
--two-stage --image photo.jpg -o out.mp4
On 32 GB Macs add --low-ram for block-streamed inference. q8 fits 16 GB with --low-ram.
The cond-safe distilled LoRA was merged into the 10Eros v1.2 bf16 base to produce a distilled bf16 checkpoint:
uv run ~/mlx-forge/scripts/merge_lora.py
# → /Volumes/Storage/10eros-v1.2-distilled-bf16.safetensors
Distilled variant + all shared components + upscalers, quantized to int8:
uv run mlx-forge convert ltx-2.3 --variant distilled-1.1 \
--checkpoint /Volumes/Storage/10eros-v1.2-distilled-bf16.safetensors \
--quantize --bits 8 \
--spatial-upscaler x2 x1.5 --temporal-upscaler x2 \
--output models/ltx-2.3-10eros-v1.2-mlx-q8
Dev variant (10Eros v1.2 base) added into the same dir, sharing the components above:
uv run mlx-forge convert ltx-2.3 --variant dev \
--checkpoint ~/mlx-forge/models/10Eros_v1.2_bf16.safetensors \
--quantize --bits 8 --skip-shared \
--output models/ltx-2.3-10eros-v1.2-mlx-q8
Distributed under the LTX-2 license. The 10Eros finetune's own terms also apply — review the upstream model card before redistribution.