LTX-2.3-fp8 Offline Setup

The fastest method for installing this model locally is by using Docker.

Make sure to follow the instructions below.

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

The smart installation system will instantly find the perfect configuration for your specific hardware.

🧾 Hash-sum — 744931a3688d69f5354e182cd70b970e • 🗓 Updated on: 2026-06-24

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Processor: next-gen chip for heavy context processing
RAM: required: 16 GB absolute minimum for small models
Storage:100 GB free space for HuggingFace cache folder
Graphics: stable 30+ tk/s at 4-bit quantization on medium setup

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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