Introducing AI Metrics

Choosing an AI model has never been more difficult.

Every month, new models launch with bigger context windows, better benchmarks, lower latency, and increasingly complex pricing. Teams are left comparing spreadsheets, reading benchmark reports, and piecing together information from multiple sources just to decide which model to use.

Today, we're introducing AI Metrics — a new way to compare, evaluate, and understand modern AI models.

One place for every important metric

AI Metrics brings together the benchmarks, specifications, and performance indicators that matter most when evaluating models.

Compare models across:

• MMLU performance

• GPQA scores

• Context window size

• Input and output pricing

• Latency

• Reasoning benchmarks

• Multimodal capabilities

• Tool calling support

Instead of jumping between model cards and documentation pages, everything is available in a single view.

Compare models side-by-side

The biggest challenge in model selection isn't finding information—it's comparing it.

AI Metrics makes it easy to place models next to each other and instantly understand the tradeoffs. Whether you're deciding between frontier models for an agent workflow or looking for the most cost-effective option for production workloads, comparisons become straightforward.

Need the highest reasoning performance? The largest context window? The lowest inference cost? AI Metrics helps you find the right answer in seconds.

Built for teams shipping AI products

Benchmarks are only useful when they help teams make decisions.

AI Metrics was designed for engineers, founders, researchers, and product teams building real AI applications. Instead of focusing on marketing claims, we focus on the data points that impact production systems.

When you're choosing a model for customer support, coding agents, document analysis, or autonomous workflows, understanding the tradeoffs matters more than ever.

Always up to date

The AI ecosystem moves fast. New releases can change the competitive landscape overnight.

AI Metrics continuously tracks the latest model releases and updates benchmark data as new information becomes available, helping teams stay informed without spending hours on research.

A better way to evaluate AI

The future of software will be powered by AI models, but selecting those models shouldn't require digging through dozens of benchmark reports.

AI Metrics gives teams a clear, centralized view of the AI landscape so they can spend less time researching and more time building.

We're excited to see how teams use AI Metrics to make smarter decisions and build better products.