DockerFit
End CUDA Version Hell

Stop Fighting with CUDA Versions.

DockerFit intelligently generates optimized Dockerfiles for PyTorch & TensorFlow based on compatibility matrices.

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AI/ML Models

PyTorch, TensorFlow, vLLM

  • ✓ Auto CUDA version matching
  • ✓ GPU driver validation
  • ✓ Image size optimization

Web Apps

Next.js, Nuxt, Remix

  • ✓ Standalone mode support
  • ✓ Monorepo auto-handling
  • ✓ Ultra-slim 100MB images

Popular Configurations

Quick access to common framework + CUDA combinations

PyTorch

PyTorch 2.9.1 + CUDA 12.8 NEW PyTorch 2.9.1 + CUDA 12.6 PyTorch 2.4.1 + CUDA 12.4 PyTorch 2.1.2 + CUDA 11.8

TensorFlow

TensorFlow 2.20 + CUDA 12.5 NEW TensorFlow 2.19 + CUDA 12.5 TensorFlow 2.17 + CUDA 12.3 TensorFlow 2.15 + CUDA 12.2

vLLM

vLLM Latest + CUDA 12.6 vLLM Blackwell + CUDA 12.8 NEW vLLM 0.6.x + CUDA 12.4 vLLM 0.5.x + CUDA 12.1

Fix Common Issues

Troubleshooting guides for frequent Docker + GPU problems

CUDA Mismatch

PyTorch compiled with different CUDA version

GPU Not Found

Docker can't access NVIDIA GPU

Out of Memory

CUDA OOM during training or inference

Why DockerFit?

Not just another Dockerfile generator — an intelligent configuration engine powered by compatibility matrices

Precise Config

Auto-derive optimal version combinations from official compatibility data

Build Optimized

BuildKit cache mounts enabled — 10x faster rebuilds

Minimal Size

Multi-stage builds + slim base images — 80%+ size reduction

Best Practices

Non-root user, cleanup, security hardening built-in