Driving innovation through emerging technologies and human-centered design. Storyteller, investor, and board member focused on creating and capturing transformative value.
Founder of DeepLearning.AI; Managing General Partner of AI Fund; Exec Chairman of Landing AI
Shoutout to the team that built https://lnkd.in/g3Y-Zj3W . Really neat site that benchmarks the speed of different LLM API providers to help developers pick which models to use. This nicely complements the LMSYS Chatbot Arena, Hugging Face open LLM leaderboards and Stanford's HELM that focus more on the quality of the outputs.
I hope benchmarks like this encourage more providers to work on fast token generation, which is critical for agentic workflows!
Founder of DeepLearning.AI; Managing General Partner of AI Fund; Exec Chairman of Landing AI
Shoutout to the team that built https://lnkd.in/g3Y-Zj3W . Really neat site that benchmarks the speed of different LLM API providers to help developers pick which models to use. This nicely complements the LMSYS Chatbot Arena, Hugging Face open LLM leaderboards and Stanford's HELM that focus more on the quality of the outputs.
I hope benchmarks like this encourage more providers to work on fast token generation, which is critical for agentic workflows!
Founder of DeepLearning.AI; Managing General Partner of AI Fund; Exec Chairman of Landing AI
Shoutout to the team that built https://lnkd.in/g3Y-Zj3W . Really neat site that benchmarks the speed of different LLM API providers to help developers pick which models to use. This nicely complements the LMSYS Chatbot Arena, Hugging Face open LLM leaderboards and Stanford's HELM that focus more on the quality of the outputs.
I hope benchmarks like this encourage more providers to work on fast token generation, which is critical for agentic workflows!
🚀 Agentic AI Trends: Benchmarking and Innovation 🧠
📊 The AI solution space is seeing increased focus on agentic-specific frameworks and even model training. From newcomers like AgentOps to LangChain's new LangGraph cloud, the industry is evolving rapidly.
Your solutions should be auditable not just for cost and standard metrics, but tools, like AgentOps are even getting into the metrics in the space of conversational context for multiple agents. (More on that in a upcoming post on Observability) (https://www.agentops.ai/)
🔍 A notable development:
New benchmarking site for LLM API providers! This tool helps developers compare:
• ⚡ Speed of different models
• 💰 Cost-effectiveness
• 🎯 Overall performance
🔗 Complements existing resources:
• LMSYS Chatbot Arena
• Hugging Face's open LLM leaderboards
Each offering unique insights into model capabilities.
💼 At Agentic Insights LLC, we're tracking these developments to help businesses optimize their AI strategies. Subscribe for more updates!
📜 https://lnkd.in/gn8EPzrS#AgenticAI#AIBenchmarking#TechInnovation
Founder of DeepLearning.AI; Managing General Partner of AI Fund; Exec Chairman of Landing AI
Shoutout to the team that built https://lnkd.in/g3Y-Zj3W . Really neat site that benchmarks the speed of different LLM API providers to help developers pick which models to use. This nicely complements the LMSYS Chatbot Arena, Hugging Face open LLM leaderboards and Stanford's HELM that focus more on the quality of the outputs.
I hope benchmarks like this encourage more providers to work on fast token generation, which is critical for agentic workflows!
Founder of DeepLearning.AI; Managing General Partner of AI Fund; Exec Chairman of Landing AI
Shoutout to the team that built https://lnkd.in/g3Y-Zj3W . Really neat site that benchmarks the speed of different LLM API providers to help developers pick which models to use. This nicely complements the LMSYS Chatbot Arena, Hugging Face open LLM leaderboards and Stanford's HELM that focus more on the quality of the outputs.
I hope benchmarks like this encourage more providers to work on fast token generation, which is critical for agentic workflows!
In the age of AI, choosing the right language model can be critical. Performance benchmarking is essential for evaluating AI models. It allows comparing different models based on factors like quality and output speed.
The findings of this analysis is quite interesting and there is a clear trade-off between model quality and output speed, with higher quality models typically having lower output speed.
Founder of DeepLearning.AI; Managing General Partner of AI Fund; Exec Chairman of Landing AI
Shoutout to the team that built https://lnkd.in/g3Y-Zj3W . Really neat site that benchmarks the speed of different LLM API providers to help developers pick which models to use. This nicely complements the LMSYS Chatbot Arena, Hugging Face open LLM leaderboards and Stanford's HELM that focus more on the quality of the outputs.
I hope benchmarks like this encourage more providers to work on fast token generation, which is critical for agentic workflows!
Why we need to know the comparison between the quality, speed and the pricing of each model ?
Answer can have a lot of details but as Aneignung, it’s for the consideration of the following factors.
Sure, here are the key points:
1. Informed Decision Making
2. Cost-Effectiveness
3. Efficiency
4. Quality Assurance
5. Competitive Advantage
6. User Satisfaction
7. Scalability and Future-Proofing
Founder of DeepLearning.AI; Managing General Partner of AI Fund; Exec Chairman of Landing AI
Shoutout to the team that built https://lnkd.in/g3Y-Zj3W . Really neat site that benchmarks the speed of different LLM API providers to help developers pick which models to use. This nicely complements the LMSYS Chatbot Arena, Hugging Face open LLM leaderboards and Stanford's HELM that focus more on the quality of the outputs.
I hope benchmarks like this encourage more providers to work on fast token generation, which is critical for agentic workflows!
The new benchmarking site (https://lnkd.in/g3Y-Zj3W) is a fantastic tool for developers to compare the speed of different LLM API providers. This complements existing resources like LMSYS Chatbot Arena, Hugging Face open LLM leaderboards, and Stanford's HELM, which focus on output quality. Faster token generation is crucial for agentic workflows.
Founder of DeepLearning.AI; Managing General Partner of AI Fund; Exec Chairman of Landing AI
Shoutout to the team that built https://lnkd.in/g3Y-Zj3W . Really neat site that benchmarks the speed of different LLM API providers to help developers pick which models to use. This nicely complements the LMSYS Chatbot Arena, Hugging Face open LLM leaderboards and Stanford's HELM that focus more on the quality of the outputs.
I hope benchmarks like this encourage more providers to work on fast token generation, which is critical for agentic workflows!
Professor in IT | Digital Trust Advocate | Passionate Educator | Energetic Mentor | Solutionist + Inventor + Researcher + IS Engineer | TEDxUSriJayewadenepura Organiser | CSSL ICT Educator of the Year 2023
Artificial Analysis provides objective benchmarks & information to support developers, customers, researchers, and other users of AI models to make informed decisions in choosing Which AI model to use for a given task, and
Which hosting provider to use to access the model.
#AI#LLMs
Founder of DeepLearning.AI; Managing General Partner of AI Fund; Exec Chairman of Landing AI
Shoutout to the team that built https://lnkd.in/g3Y-Zj3W . Really neat site that benchmarks the speed of different LLM API providers to help developers pick which models to use. This nicely complements the LMSYS Chatbot Arena, Hugging Face open LLM leaderboards and Stanford's HELM that focus more on the quality of the outputs.
I hope benchmarks like this encourage more providers to work on fast token generation, which is critical for agentic workflows!
Founder of DeepLearning.AI; Managing General Partner of AI Fund; Exec Chairman of Landing AI
Shoutout to the team that built https://lnkd.in/g3Y-Zj3W . Really neat site that benchmarks the speed of different LLM API providers to help developers pick which models to use. This nicely complements the LMSYS Chatbot Arena, Hugging Face open LLM leaderboards and Stanford's HELM that focus more on the quality of the outputs.
I hope benchmarks like this encourage more providers to work on fast token generation, which is critical for agentic workflows!
Founder of DeepLearning.AI; Managing General Partner of AI Fund; Exec Chairman of Landing AI
Shoutout to the team that built https://lnkd.in/g3Y-Zj3W . Really neat site that benchmarks the speed of different LLM API providers to help developers pick which models to use. This nicely complements the LMSYS Chatbot Arena, Hugging Face open LLM leaderboards and Stanford's HELM that focus more on the quality of the outputs.
I hope benchmarks like this encourage more providers to work on fast token generation, which is critical for agentic workflows!