正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

Introducing Smart Routing in Unity AI Gateway. Stop overpaying for AI. Smart Routing matches each coding task to the right model and harness based on what the task needs, so higher-cost models can differentiate on intelligence while lower-cost models differentiate on cost and performance. Match frontier quality and cut... show more

Databricks

96,288 subscribers

124,015 次观看 • 10 天前 •via X (Twitter)

科学技术教育新闻政治

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

Agent Categories and Costs are now in the Agent Leaderboard! Two questions guide model selection: task-specific performance and cost to completion. Based on analysis of 1.7M+ real-world Agent Mode sessions, the leaderboard now lets users: - Filter the leaderboard by Code, Work, and Chat to compare model performance by task type - View real cost-per-task for each model, including the Pareto frontier of the most cost-efficient options at each performance level

Agent Categories and Costs are now in the Agent Leaderboard! Two questions guide model selection: task-specific performance and cost to completion. Based on analysis of 1.7M+ real-world Agent Mode sessions, the leaderboard now lets users: - Filter the leaderboard by Code, Work, and Chat to compare model performance by task type - View real cost-per-task for each model, including the Pareto frontier of the most cost-efficient options at each performance level

Arena.ai

29,096 次观看 • 6 天前

Introducing model routing to Factory. Factory Router picks the right model for every task, automatically. Maintain frontier performance while cutting costs by 25%.

Introducing model routing to Factory. Factory Router picks the right model for every task, automatically. Maintain frontier performance while cutting costs by 25%.

Factory

2,250,302 次观看 • 2 个月前

Introducing Entelligence AI Model Router, dynamic turn based routing trained on engineering tasks that cuts costs by over 50% Automatically route every coding turn to the model with the best balance of quality, latency, and cost. Escalate to frontier models when they’re actually needed Balanced mode reduces spend by 46% per session Eco mode helps teams save > 76%

Introducing Entelligence AI Model Router, dynamic turn based routing trained on engineering tasks that cuts costs by over 50% Automatically route every coding turn to the model with the best balance of quality, latency, and cost. Escalate to frontier models when they’re actually needed Balanced mode reduces spend by 46% per session Eco mode helps teams save > 76%

Aiswarya Sankar

81,455 次观看 • 1 个月前

The right model depends on the task. NVIDIA NeMo Switchyard helps developers route each agent workflow step across a chosen model pool based on their own quality, latency and cost criteria. Kari Briski joins MTS to explain why agent workflows need model routing.

The right model depends on the task. NVIDIA NeMo Switchyard helps developers route each agent workflow step across a chosen model pool based on their own quality, latency and cost criteria. Kari Briski joins MTS to explain why agent workflows need model routing.

NVIDIA

91,253 次观看 • 3 天前

Introducing the Morph Model Router. It chooses the best model for each task in under 50ms. Keep frontier performance while lowering latency and cost. Available today in our API

Introducing the Morph Model Router. It chooses the best model for each task in under 50ms. Keep frontier performance while lowering latency and cost. Available today in our API

Morph

20,281 次观看 • 2 个月前

We just cut AI spend by 75% across an entire workforce in one click. Introducing: Merge for Workforce. Without Merge, your employees are left choosing one of two options: 1. Spend 100x the cost they should be from using frontier models for everything 2. Deliver subpar work from overly restrictive model access Instead with Merge, IT can connect any identity provider and set model routing policies by team in one click. Merge pushes them to every machine through a desktop client, overriding the model configs across your team’s AI assistants and coding tools. Now every task gets the right model for the job. The result? 75x fewer tokens with faster and better output.

We just cut AI spend by 75% across an entire workforce in one click. Introducing: Merge for Workforce. Without Merge, your employees are left choosing one of two options: 1. Spend 100x the cost they should be from using frontier models for everything 2. Deliver subpar work from overly restrictive model access Instead with Merge, IT can connect any identity provider and set model routing policies by team in one click. Merge pushes them to every machine through a desktop client, overriding the model configs across your team’s AI assistants and coding tools. Now every task gets the right model for the job. The result? 75x fewer tokens with faster and better output.

Shensi Ding

451,754 次观看 • 6 天前

Introducing EVO Router - a smart router that continuously optimizes and hill-climbs on your AI inference workloads. It learns from your code, prompts, production traffic, use cases, and SLAs, then searches for the best setup for every workload. That can mean more than choosing just a single model or routing through a classifier. EVO (YC F26) can optimize across model × provider combinations, fusion systems, cascades, routing policies, and prompts — whatever the workload allows, while staying within your quality, latency, and reliability constraints. As open-source models move closer to frontier-model performance, we believe this kind of workload-specific hill-climbing will become an important part of how AI systems are deployed and operated. Our early users have seen 30–60% lower inference costs across use cases ranging from complex multi-turn agents to asynchronous batch workloads. EVO Router has also reached the Pareto frontier on several benchmarks, outperforming existing setups on cost, quality, or both.

Introducing EVO Router - a smart router that continuously optimizes and hill-climbs on your AI inference workloads. It learns from your code, prompts, production traffic, use cases, and SLAs, then searches for the best setup for every workload. That can mean more than choosing just a single model or routing through a classifier. EVO (YC F26) can optimize across model × provider combinations, fusion systems, cascades, routing policies, and prompts — whatever the workload allows, while staying within your quality, latency, and reliability constraints. As open-source models move closer to frontier-model performance, we believe this kind of workload-specific hill-climbing will become an important part of how AI systems are deployed and operated. Our early users have seen 30–60% lower inference costs across use cases ranging from complex multi-turn agents to asynchronous batch workloads. EVO Router has also reached the Pareto frontier on several benchmarks, outperforming existing setups on cost, quality, or both.

Alok Bishoyi

15,572 次观看 • 20 天前

The most effective AI systems don't rely on a single model. Frontier models provide state-of-the-art performance for complex tasks, while routers automatically select lightweight, open-source models for simpler jobs to optimize accuracy, latency, and cost. Learn more:

The most effective AI systems don't rely on a single model. Frontier models provide state-of-the-art performance for complex tasks, while routers automatically select lightweight, open-source models for simpler jobs to optimize accuracy, latency, and cost. Learn more:

NVIDIA AI

12,152 次观看 • 5 个月前

Introducing Exa Agent: frontier web research at less than half the cost of GPT 5.5 and Opus. /agent orchestrates a mixture of cost-effective models to complete any web research task, from simple data enrichments to building gigantic lists.

Introducing Exa Agent: frontier web research at less than half the cost of GPT 5.5 and Opus. /agent orchestrates a mixture of cost-effective models to complete any web research task, from simple data enrichments to building gigantic lists.

Exa

1,066,042 次观看 • 2 个月前

What is the best LLM for agentic software engineering? Today, we're releasing The OpenHands Index to answer this question. It's the first broad-coverage benchmark for AI coding agents, comparing them on accuracy, cost, and runtime across 5 task domains.

What is the best LLM for agentic software engineering? Today, we're releasing The OpenHands Index to answer this question. It's the first broad-coverage benchmark for AI coding agents, comparing them on accuracy, cost, and runtime across 5 task domains.

OpenHands

31,780 次观看 • 6 个月前

Stop hardcoding one model name in your code. Now you can give each request a policy: a small rule for what the call needs It picks the right model for the job, on your own keys This is unhardcoded, our new open source routing for AI models, live today

Stop hardcoding one model name in your code. Now you can give each request a policy: a small rule for what the call needs It picks the right model for the job, on your own keys This is unhardcoded, our new open source routing for AI models, live today

GenLayer

94,570 次观看 • 2 个月前

"Most enterprise workflows don't require frontier AI models. Outside of coding, tasks like summarization, document generation, and briefing can often be handled effectively by lower-cost open-source models. The real value is knowing when you need frontier performance and when cheaper models are more than good enough." Michael Mignano What percent of enterprise workflows requires frontier models today Nikesh Arora Matan Grinberg Aaron Katz Lin Qiao

"Most enterprise workflows don't require frontier AI models. Outside of coding, tasks like summarization, document generation, and briefing can often be handled effectively by lower-cost open-source models. The real value is knowing when you need frontier performance and when cheaper models are more than good enough." Michael Mignano What percent of enterprise workflows requires frontier models today Nikesh Arora Matan Grinberg Aaron Katz Lin Qiao

Harry Stebbings

36,428 次观看 • 1 个月前

We just built the #1 tool every AI team wants. Introducing Merge Gateway: LLM routing, fallback, cost guardrails, and security, all in one place. Everyone gets $10 free LLM usage on us to try it out. RT+ comment “Gateway” → we’ll double your credits.

We just built the #1 tool every AI team wants. Introducing Merge Gateway: LLM routing, fallback, cost guardrails, and security, all in one place. Everyone gets $10 free LLM usage on us to try it out. RT+ comment “Gateway” → we’ll double your credits.

Shensi Ding

100,066 次观看 • 4 个月前

Claude Code can now work with 50+ AI models. Zen MCP connects Claude Code with Gemini, OpenAI, Grok, and local models using Ollama for the best analysis on each task. 100% Opensource.

Claude Code can now work with 50+ AI models. Zen MCP connects Claude Code with Gemini, OpenAI, Grok, and local models using Ollama for the best analysis on each task. 100% Opensource.

Shubham Saboo

39,748 次观看 • 10 个月前

Before Allora, AI was model centric, forcing teams to chase and maintain the “right” model for every task. After Allora, Users set the goal and Allora Network coordinates thousands of models in real time for the best output. Allora Mainnet is the shift the age of intelligence needs.

Before Allora, AI was model centric, forcing teams to chase and maintain the “right” model for every task. After Allora, Users set the goal and Allora Network coordinates thousands of models in real time for the best output. Allora Mainnet is the shift the age of intelligence needs.

Allora

79,895 次观看 • 9 个月前

Introducing Cline (formerly Claude Dev), an AI assistant that can use your CLI aNd Editor. v2.0 brings exciting updates: responses are now streamed into your editor, a cancel button for better control over tasks, a new XML-based tool calling prompt resulting in ~40% fewer requests per task + better performance from non-Claude models, search and use any model on OpenRouter (search “free” for no-cost options). More details and benchmarks in the release notes:

Introducing Cline (formerly Claude Dev), an AI assistant that can use your CLI aNd Editor. v2.0 brings exciting updates: responses are now streamed into your editor, a cancel button for better control over tasks, a new XML-based tool calling prompt resulting in ~40% fewer requests per task + better performance from non-Claude models, search and use any model on OpenRouter (search “free” for no-cost options). More details and benchmarks in the release notes:

Saoud Rizwan

54,723 次观看 • 1 年前

Introducing NVIDIA Nemotron 3 Ultra. A frontier smart open model built for long-running agents that need to plan, reason, use tools and keep working across complex coding, research and enterprise workflows. Up to 5x faster inference and up to 30% lower cost for agentic tasks. Learn more:

Introducing NVIDIA Nemotron 3 Ultra. A frontier smart open model built for long-running agents that need to plan, reason, use tools and keep working across complex coding, research and enterprise workflows. Up to 5x faster inference and up to 30% lower cost for agentic tasks. Learn more:

NVIDIA

228,735 次观看 • 2 个月前

We’re launching Optima. Now anyone can create a custom benchmark for their use case, leveraging Artificial Analysis’ leading research and platform Building and running benchmarks is difficult. We have distilled Artificial Analysis’ research and experience developing benchmarks into Optima, a new platform for benchmarking models on your own workloads and comparing performance, speed and cost efficiency. Optima allows you to find the best model for your task, or an equally performant alternative to your current setup at 10x lower cost or time per task. We’ve integrated Artificial Analysis' research and experience in benchmarks across the Optima workflow: ➤ Build benchmarks based on your own data and use cases: There are three ways to build a benchmark with Optima. Upload an existing evaluation dataset from your own files or Hugging Face, or import agent traces from platforms including Arize AI, Braintrust and langfuse.com. Install the Optima skill to build a benchmark using context from your coding environment and previous sessions. Or simply describe your use case and provide example inputs and outputs, and Optima will build the benchmark for you ➤ Run across the latest models: Run the same benchmark across leading models in a single click, and keep your leaderboard up to date as soon as new models are released ➤ Bring Artificial Analysis grading to your own benchmark: Evaluate responses against objective rubric criteria or using the same pairwise judging approach used for Artificial Analysis benchmarks including GDPval-AA and AA-Briefcase. For pairwise judging, select your preferred responses from a sample and Optima uses those preferences to rank models across your test set ➤ Compare performance, cost and time efficiency: Optima measures more than model performance. Cost per Task and Time per Task are tracked alongside benchmark scores, with category-level results and support for custom metrics, allowing you to compare the tradeoffs between models for your specific use case Ahead of launch, here are examples questions our beta testers answered with Optima: ➤ Which model can save me 10x the cost without a meaningful decrease in quality for my finance & accounting agent? ➤ Which model best matches the writing style of lawyers for my legal agent? ➤ Which model can best identify different elements in my custom image dataset? Optima is available today. Build your own benchmark at

We’re launching Optima. Now anyone can create a custom benchmark for their use case, leveraging Artificial Analysis’ leading research and platform Building and running benchmarks is difficult. We have distilled Artificial Analysis’ research and experience developing benchmarks into Optima, a new platform for benchmarking models on your own workloads and comparing performance, speed and cost efficiency. Optima allows you to find the best model for your task, or an equally performant alternative to your current setup at 10x lower cost or time per task. We’ve integrated Artificial Analysis' research and experience in benchmarks across the Optima workflow: ➤ Build benchmarks based on your own data and use cases: There are three ways to build a benchmark with Optima. Upload an existing evaluation dataset from your own files or Hugging Face, or import agent traces from platforms including Arize AI, Braintrust and langfuse.com. Install the Optima skill to build a benchmark using context from your coding environment and previous sessions. Or simply describe your use case and provide example inputs and outputs, and Optima will build the benchmark for you ➤ Run across the latest models: Run the same benchmark across leading models in a single click, and keep your leaderboard up to date as soon as new models are released ➤ Bring Artificial Analysis grading to your own benchmark: Evaluate responses against objective rubric criteria or using the same pairwise judging approach used for Artificial Analysis benchmarks including GDPval-AA and AA-Briefcase. For pairwise judging, select your preferred responses from a sample and Optima uses those preferences to rank models across your test set ➤ Compare performance, cost and time efficiency: Optima measures more than model performance. Cost per Task and Time per Task are tracked alongside benchmark scores, with category-level results and support for custom metrics, allowing you to compare the tradeoffs between models for your specific use case Ahead of launch, here are examples questions our beta testers answered with Optima: ➤ Which model can save me 10x the cost without a meaningful decrease in quality for my finance & accounting agent? ➤ Which model best matches the writing style of lawyers for my legal agent? ➤ Which model can best identify different elements in my custom image dataset? Optima is available today. Build your own benchmark at

Artificial Analysis

130,269 次观看 • 11 天前

Monitor and control your AI spend on every provider on Our early users save 40% on average. Every week, the price-intelligence-latency frontier shifts, and we expect this trend to continue. Tradeoffs between latency, reasoning, cost, service tier, open source and closed source models are shifting constantly. Router sends every request to the model that's actually best for the task and helps you control what tokens you buy. We benchmark it against real work: ~40% lower cost for the same outputs. Today we're opening it to everyone. Two lines of code or just change your base URL. No Ramp account needed. Free through 2026, first $26 on us. Get an API key today at

Monitor and control your AI spend on every provider on Our early users save 40% on average. Every week, the price-intelligence-latency frontier shifts, and we expect this trend to continue. Tradeoffs between latency, reasoning, cost, service tier, open source and closed source models are shifting constantly. Router sends every request to the model that's actually best for the task and helps you control what tokens you buy. We benchmark it against real work: ~40% lower cost for the same outputs. Today we're opening it to everyone. Two lines of code or just change your base URL. No Ramp account needed. Free through 2026, first $26 on us. Get an API key today at

Veeral Patel

1,391,113 次观看 • 4 天前

Newly released ✧ Gemma 4 is live on AI/ML API. We ran a benchmark test to showcase model capabilities on a complex analysis task, delivering stunning gains in speed, cost, and quality. RT + comment to win $100 API tokens - 50 random winners!

Newly released ✧ Gemma 4 is live on AI/ML API. We ran a benchmark test to showcase model capabilities on a complex analysis task, delivering stunning gains in speed, cost, and quality. RT + comment to win $100 API tokens - 50 random winners!

AI/ML API

26,455 次观看 • 4 个月前