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GPU Python packages
that just install.

Pre-built CUDA wheels for flash-attn, deepspeed, mamba-ssm, and 7 more packages.
One command. No compiling.

bash
$ easywheels install flash-attn
Detected: Python 3.12, CUDA 12.8, RTX 4090 (sm_89), torch 2.9
Resolving flash-attn...
Found: flash_attn-2.8.3+cu128torch2.9-cp312-cp312-linux_x86_64.whl
Downloading flash_attn-2.8.3 (250.7 MB)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 250.7/250.7 MB 9.2s
Successfully installed flash-attn-2.8.3
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flash-attn flash-attn-3 deepspeed mamba-ssm causal-conv1d llama-cpp-python exllamav2 gptqmodel sageattention flashinfer flash-attn flash-attn-3 deepspeed mamba-ssm causal-conv1d llama-cpp-python exllamav2 gptqmodel sageattention flashinfer

You know the drill.

45+ minutes

Average compile time for flash-attn from source. Per environment. Per CUDA version.

CUDA mismatch

Wrong toolkit version? Incompatible driver? Start over from scratch.

cmake errors

Missing headers, broken builds, cryptic C++ template errors three screens long.

45 min

Build from source

9 seconds

EasyWheels

flash-attn 2.8.3 on Python 3.12. Measured on a real install.

Every ML developer has lost an afternoon to this.
We built EasyWheels so you never have to again.

Three steps.
Seriously, that's it.

01

Install the CLI

$ pip install easywheels
$ easywheels login

One-time setup. Auto-detects your environment.

02

Install any package

$ easywheels install flash-attn

Detects your Python, CUDA, GPU, and torch version. Picks the exact right wheel.

03

Done in seconds

flash-attn 2.8.3 installed (3.2s)

Pre-compiled wheel. No cmake. No waiting.

Start free. Scale when you're ready.

14-day trial. 3 downloads. No credit card required.

Early supporter rates — locked in for founding members. Prices will increase as the registry grows.

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  • 3 downloads included
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Or pay per download — $2/wheel, no subscription needed.

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