metadata
library_name: tensorrt-rtx
license: apache-2.0
base_model: black-forest-labs/FLUX.1-schnell
tags:
- tensorrt-rtx
- flux1
- fp8
- schnell
- optimized
inference: false
FLUX1 TensorRT-RTX: SCHNELL-Fp8 🔨 Building
Optimized TensorRT-RTX engines for FLUX1 on Fp8 architecture with SCHNELL quantization.
🎯 This Repository
One variant, one download - only get exactly what you need!
- Model: FLUX1
- Architecture: Fp8 (Compute Capability 8.0+)
- Quantization: SCHNELL
- Memory: TBD
- Speed: TBD for 1024x1024 generation
🚀 Quick Start
Automatic (Recommended)
# ImageAI server downloads automatically
curl -X POST "http://localhost:8001/generate" \
-H "Content-Type: application/json" \
-d '{
"prompt": "a beautiful landscape",
"model": "flux1-tensorrt_rtx:schnell",
"width": 1024,
"height": 1024
}'
Manual Download
from huggingface_hub import snapshot_download
# Download this specific variant only
engines_path = snapshot_download(
repo_id="imgailab/flux1-trtx-schnell-fp8-blackwell"
)
# Engines are in: engines_path/engines/*.plan
Direct Integration
from imageai_server.tensorrt.nvidia_sdxl_pipeline import NVIDIASDXLPipeline
pipeline = NVIDIASDXLPipeline()
pipeline.load_engines(
engine_dir=f"{engines_path}/engines",
framework_model_dir=f"{engines_path}/framework",
onnx_dir=f"{engines_path}/onnx"
)
pipeline.activate_engines()
images, time_ms = pipeline.infer(
prompt="a serene mountain landscape",
height=1024,
width=1024
)
📊 Performance
| Metric | Value |
|---|---|
| Memory Usage | TBD |
| Inference Speed | TBD |
| Resolution | 1024x1024 (optimized) |
| Batch Size | 1 (optimized) |
| Precision | SCHNELL |
🔧 Requirements
Hardware
- GPU: Fp8 architecture
- Ampere: RTX 3090, A100, etc.
- Ada Lovelace: RTX 4090, etc.
- Blackwell: H200, etc.
- VRAM: TBD minimum
- Compute Capability: 8.0+
Software
- TensorRT-RTX: 1.0.0.21+
- CUDA: 12.0+
- Python: 3.8+
📁 Repository Structure
flux1-trtx-schnell-fp8-blackwell/
├── engines/ # TensorRT engine files
│ ├── *.plan # Optimized engines
├── config.json # Configuration metadata
└── README.md # This file
🌐 Related Repositories
Other variants for FLUX1:
- Ampere BF16\n- Ada FP8\n- Ada BF16\n- Blackwell FP4\n- Blackwell FP8\n- Blackwell BF16\n
📝 License
Inherits license from base model: black-forest-labs/FLUX.1-schnell
🔄 Updates
- 2025-08-12: Initial release
- Optimized for single-variant downloads
Part of the ImageAI TensorRT-RTX engine collection