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Visualization of GPT-4o breaking away from the quality & speed trade-off curve the LLMs have followed thus far ✂️
Visualization of GPT-4o breaking away from the quality & speed trade-off curve the LLMs have followed thus far ✂️
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Key GPT-4o takeaways
Key GPT-4o takeaways
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‣ GPT-4o not only offers the highest quality, it also sits amongst the fastest LLMs
‣ GPT-4o not only offers the highest quality, it also sits amongst the fastest LLMs
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‣ For those with speed/latency-sensitive use cases, where previously Claude 3 Haiku or Mixtral 8x7b were leaders, GPT-4o is now a compelling option (though significantly more expensive)  
‣ For those with speed/latency-sensitive use cases, where previously Claude 3 Haiku or Mixtral 8x7b were leaders, GPT-4o is now a compelling option (though significantly more expensive)  
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‣ Previously Groq was the only provider to break from the curve using its own LPU chips. OpenAI has done it on Nvidia hardware (one can imagine the potential for GPT-4o on Groq)
‣ Previously Groq was the only provider to break from the curve using its own LPU chips. OpenAI has done it on Nvidia hardware (one can imagine the potential for GPT-4o on Groq)
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👉 How did they do it? Will follow up with more analysis on this but potential approaches include a very large but sparse MoE model (similar to Snowflake's Arctic) and improvements in data quality (likely to have driven much of Llama 3's impressive quality relative to parameter count)
👉 How did they do it? Will follow up with more analysis on this but potential approaches include a very large but sparse MoE model (similar to Snowflake's Arctic) and improvements in data quality (likely to have driven much of Llama 3's impressive quality relative to parameter count)
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Notes: Throughput represents the median across providers over the last 14 days of measurements (8x per day)
Notes: Throughput represents the median across providers over the last 14 days of measurements (8x per day)
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Data is present on our HF leaderboard: 
Data is present on our HF leaderboard: 
resource
https://huggingface.co/spaces/ArtificialAnalysis/LLM-Performance-Leaderboard
space
ArtificialAnalysis/LLM-Performance-Leaderboard
https://huggingface.co/spaces/ArtificialAnalysis/LLM-Performance-Leaderboard
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 and graphs present on our website
 and graphs present on our website
Visualization of GPT-4o breaking away from the quality & speed trade-off curve the LLMs have followed thus far ✂️

Key GPT-4o takeaways
‣ GPT-4o not only offers the highest quality, it also sits amongst the fastest LLMs
‣ For those with speed/latency-sensitive use cases, where previously Claude 3 Haiku or Mixtral 8x7b were leaders, GPT-4o is now a compelling option (though significantly more expensive)  
‣ Previously Groq was the only provider to break from the curve using its own LPU chips. OpenAI has done it on Nvidia hardware (one can imagine the potential for GPT-4o on Groq)

👉 How did they do it? Will follow up with more analysis on this but potential approaches include a very large but sparse MoE model (similar to Snowflake's Arctic) and improvements in data quality (likely to have driven much of Llama 3's impressive quality relative to parameter count)

Notes: Throughput represents the median across providers over the last 14 days of measurements (8x per day)

Data is present on our HF leaderboard: https://huggingface.co/spaces/ArtificialAnalysis/LLM-Performance-Leaderboard and graphs present on our website
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