What is ThunderKittens 2.0?

Stanford's open-source library for ultra-fast transformer kernels on NVIDIA GPUs, fusing ops to cut latency by 2x.

Does ThunderKittens 2.0 work on RTX GPUs?

Absolutely — optimized for 30/40-series, with A100/V100 support too.

How do I install ThunderKittens 2.0?

`pip install thunderkittens` then swap your model's forward() — docs cover it in 5 lines.

ThunderKittens 2.0 Unleashes Blazing GPU Kernels

ThunderKittens 2.0 isn't just faster—it's a blueprint for squeezing every flop from your GPU. Stanford's Hazy Research just rewrote the rules for transformer kernels.

theAIcatchup Apr 08, 2026 4 min read

ThunderKittens 2.0 benchmark charts showing 2x speedups on RTX 4090 and A100 GPUs

⚡ Key Takeaways

ThunderKittens 2.0 fuses kernels for 2x faster transformer inference on consumer GPUs. 𝕏
Triton-powered autotuning makes it plug-and-play for PyTorch users. 𝕏
Democratizes high-perf AI, challenging cloud dependency with local runs. 𝕏

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theAIcatchup

Community-driven. Code-first.

#AI inference #FlashAttention #GPU kernels #Hazy Research #Stanford Hazy Research #ThunderKittens 2.0 #transformer inference #transformer optimization

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Originally reported by Reddit r/programming

⚡ Key Takeaways

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