atomic.chat(@atomic_chat_hq):TensorRT 206% faster than llama.cpp ✳️ We wired @NVIDIAAI's TensorRT into Atomic Chat's engine and tested Qwen3.5-4B/Qwen 3-8B via CUDA on a Blackwell RTX 5090, measuring 3.43s vs 10.49s with llama.cpp Run AI models locally -> https://t.co/RbcCOIgVkj

atomic.chat

@atomic_chat_hq

The simplest way to run open models on any hardware. Powered by TurboQuant. Team: @gladkos @skinbagwbones @AlexFromAtomic @danyurkin @quantizedden

参加 March 2026

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atomic.chat@atomic_chat_hq

2026.10.05 22:59

TensorRT 206% faster than llama.cpp ✳️ We wired @NVIDIAAI's TensorRT into Atomic Chat's engine and tested Qwen3.5-4B/Qwen 3-8B via CUDA on a Blackwell RTX 5090, measuring 3.43s vs 10.49s with llama.cpp Run AI models locally ->

NVIDIA RTX Spark@NVIDIARTXSpark

2026.10.01 21:30

What could your app do with local AI? 🤔 Turn speech into text, select objects in video, or create images from a prompt. Our latest blog walks through open-source C++ samples that bring these capabilities to @Windows and Linux with NVIDIA TensorRT RTX.