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Model: "rene-1.3b"
Cerebras Inference: Faster, Better, AND Cheaper
llama-3.1-8b llama-3.1-70b gemini-1.5-flash gemini-1.5-pro cogvideox-5b mamba-2 rene-1.3b llama-3.1 gemini-1.5 claude groq cerebras cursor google-deepmind anthropic inference-speed wafer-scale-chips prompt-caching model-merging benchmarking open-source-models code-editing model-optimization jeremyphoward sam-altman nat-friedman daniel-gross swyx
Groq led early 2024 with superfast LLM inference speeds, achieving ~450 tokens/sec for Mixtral 8x7B and 240 tokens/sec for Llama 2 70B. Cursor introduced a specialized code edit model hitting 1000 tokens/sec. Now, Cerebras claims the fastest inference with their wafer-scale chips, running Llama3.1-8b at 1800 tokens/sec and Llama3.1-70B at 450 tokens/sec at full precision, with competitive pricing and a generous free tier. Google's Gemini 1.5 models showed significant benchmark improvements, especially Gemini-1.5-Flash and Gemini-1.5-Pro. New open-source models like CogVideoX-5B and Mamba-2 (Rene 1.3B) were released, optimized for consumer hardware. Anthropic's Claude now supports prompt caching, improving speed and cost efficiency. "Cerebras Inference runs Llama3.1 20x faster than GPU solutions at 1/5 the price."