Groq Inc. has made significant advancements in AI language modeling, particularly with the Llama3 models. The company has achieved an input rate of 40,792 tokens per second on the Llama3 70B model, utilizing FP16 multiply and FP32 accumulate operations. This follows their previous milestone of 30,000 tokens per second on the Llama3 8B model. These improvements are attributed to Groq's innovative approach, which includes the elimination of MatMul operations in favor of addition and negation operations. This method has not only maintained strong performance at billion-parameter scales but also reduced memory usage by up to 61%. Groq's technology demonstrates impressive inference speed and precision, processing approximately 8,000 tokens in 0.2 seconds with lossless precision. Additionally, Groq has achieved over 1200 tps on L3 8B, operating at 13W, moving LLMs closer to brain-like efficiency.
Put this mind bending achievement in perspective: @GroqInc runs Llama 70b in lossless precision on ~4 Wikipedia articles in quite literally the blink of an eye. - A 70B model in 16-bit precision with 32-bit accumulation (loss-less). - Processing ~8000 tokens in 0.2 seconds (or… https://t.co/N1arORIsf5
Scalable MatMul-free Language Modeling MatMul operations are replaced with addition and negation operations >We processed billion-parameter scale models at 13W beyond human readable throughput, moving LLMs closer to brain-like efficiency https://t.co/6PrSlEPlIY
40k tok/s input on llama3 8b. AI workloads are generally very input heavy. This, combined with our output speed will now make @GroqInc the only way to build performant AI applications. Some realtime feedback from a happy user: https://t.co/vTB4YnJ5Zd https://t.co/ktsGVwGjsB
40k tok/s input on llama3 8b. AI workloads are generally input very heavy. This combined with our output speed will now make @GroqInc the only way to build performant AI applications. Some realtime feedback from a happy user: https://t.co/CtGXV2aYrb https://t.co/ktsGVwGjsB
CompSci Paper of the Day, Issue 33: Scalable MatMul-free Language Modeling 1/4 🧵 https://t.co/aNqSme85J5
Last Week: Groq exceeded 30,000 Tokens / second input rate on Llama3 8B❗️ This Week: Llama3 70B at 40,792 Tokens/s input rate‼️ - FP16 Multiply, FP32 Accumulate - 7989 tokens in - full Llama context length Next Week: ...? 😮 https://t.co/rIijD2Is76
When it comes to precision and accuracy, we have another super power @GroqInc 🎯 https://t.co/OGgmX2vypO
Pace of @GroqInc’s improvement is really impressive 1200+ tps on L3 8B Remember, they still can stack on a ton of software efficiencies https://t.co/zQMx7zkIDj https://t.co/AQ4hxZeYuL
At a glance: inference speed 👇🏻 @GroqInc 🔥🚀 https://t.co/TnU7Unz7Wd
Scalable MatMul-free Language Modeling - Shows that MatMul operations can be completely eliminated from LLMs while maintaining strong performance at billion-parameter scales - Provides a GPU-efficient implementation of this model which reduces memory usage by up to 61% over an… https://t.co/YxeCPLn2xF