How to Run LTX-2.3-fp8 Windows 11 Quantized GGUF Direct EXE Setup Windows

How to Run LTX-2.3-fp8 Windows 11 Quantized GGUF Direct EXE Setup Windows

Deploying this model locally is quickest when done via Docker.

Please follow the instructions listed below to get started.

1-click setup: the app automatically fetches the large weight files.

Once launched, the setup wizard will detect your specs to configure the model for maximum efficiency.

🧩 Hash sum → 2d623692f1d19edd28dcd9cb3f772ce6 — Update date: 2026-06-26



  • Processor: Intel i7 / Ryzen 7 for heavy Quantized models
  • RAM: 32 GB or higher for smooth 32k context lengths
  • Disk: high-speed SSD 120 GB to cache model layers
  • GPU: high memory bandwidth GPU for next-gen local AI pipeline

LTX-2.3-fp8 is a state‑of‑the‑art language model optimized for low‑precision inference. It features a parameter count of 7 B weights and achieves high throughput on consumer‑grade GPUs. The model leverages FP8 quantization to reduce memory footprint while preserving nearly full‑precision performance. Its architecture incorporates a refined attention mechanism that cuts latency by 30 % compared to previous versions. A comparison table below highlights key metrics against earlier LTX releases.

Metric LTX-2.3-fp8 LTX-2.2-fp8
Parameters 7 B 5 B
FP8 Memory 14 GB 10 GB
Inference Latency (ms) 12 18
Throughput (tokens/s) 85 60
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