Setup LTX-2 Windows 11 with Native FP4 Step-by-Step

Running this model locally is fastest when deployed through Docker.

Review and follow the instructions below.

Then, simply start the container with the provided Docker command.

🔐 Hash sum: 541480e8c586029353b27be43a07d976 | 📅 Last update: 2026-06-25



  • CPU: modern architecture (Zen 3 / Alder Lake minimum)
  • RAM: 32 GB highly recommended for 26B+ GGUF models
  • Disk Space: free: 80 GB on system drive for scratch space
  • Graphics: stable 30+ tk/s at 4-bit quantization on medium setup

The LTX-2 model introduces a refined transformer architecture that significantly boosts contextual understanding across text and image inputs. Its training pipeline leverages a diverse dataset comprising billions of paired examples, enabling multimodal coherence that outperforms previous models. By incorporating efficient attention mechanisms, LTX-2 achieves real-time inference with minimal latency, making it suitable for production environments. The model also features an advanced reasoning layer that enhances logical consistency and reduces hallucination rates. These capabilities are summarized in the table below, which compares key performance metrics against earlier versions. Overall, LTX-2 sets a new benchmark for scalable and robust AI systems.

SpecificationValue
Parameters12B
Training Data2.5TB multimodal
Inference Latency<0.5s
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