Eight prebuilt, CUDA-optimized Python wheels for every GPU Google Colab offers — A100, L4, and T4. No more hours compiling from source. No more dependency hell. One pip install and you're running in 60 seconds.
Flash Attention 2 — the fastest path to efficient transformer inference.
v2.8.3Memory-efficient attention and transformer building blocks from Meta.
v0.0.35NVIDIA's differentiable rasterizer for 3D deep learning pipelines.
v0.4.0CUDA-accelerated mesh processing for high-performance 3D work.
v0.0.1Flexible GEMM kernels for mixed-precision compute on Ampere+.
v0.0.1CUDA voxel utilities for 3D generation and reconstruction.
v0.0.1Neural rendering components for inverse graphics and reconstruction.
v0.0.03D math and geometry utilities with CUDA acceleration.
v0.0.2| Spec | Guaranteed |
|---|---|
| GPU | A100 L4 T4 |
| Platform | Google Colab linux x86_64 |
| Python | 3.12 |
| CUDA | 12.8 |
| PyTorch | 2.10 |
80GB HBM2e. The powerhouse for large-model inference, 3D generation, and research workloads.
24GB GDDR6. Efficient inference GPU with great performance-per-watt for production tasks.
16GB GDDR6. Available on Colab free tier — perfect for prototyping and smaller workloads.
One-time $17 payment via Stripe. You get a personal token emailed instantly — no account needed.
Paste one line into your Colab notebook. All wheels download and install in seconds, not hours.
That's it. Your GPU time goes to inference and generation — not compiling gcc and nvcc from source.
State-of-the-art image-to-3D generation from Microsoft Research. Upload any image and get a high-quality 3D model in about 60 seconds on an A100 — powered entirely by the Colab Survival Pack wheels.
Every minute your GPU spends compiling is money wasted. The Colab Survival Pack pays for itself on the first run.