@ArizePhoenix: Phoenix 17.7.0 makes your token usage legible. New token detail charts break prompt + completion tokens into their part…
Summary
Phoenix 17.7.0 adds token detail charts that break down prompt and completion tokens into subcategories, with pan, zoom, and live-stream capabilities for better observability of AI model token usage.
View Cached Full Text
Cached at: 06/18/26, 10:06 AM
Phoenix 17.7.0 makes your token usage legible.
New token detail charts break prompt + completion tokens into their parts, over time: • Prompt → input, cache read, cache write, audio • Completion → output, reasoning, audio
See your cache read rates and watch reasoning-token usage trend as you tune models and thinking budgets - whatever parts your model reports, plotted as their own series.
And you can now pan, zoom & live-stream any time range right from the dashboard toolbar - no reopening the picker.
Similar Articles
@ArizePhoenix: Experiment Baselining and Charts When trying to determine if a new model is up to the task, you need to factor in many …
Phoenix now includes customizable experiment charts and baselining, allowing users to compare models along performance, latency, tokens, and cost dimensions, and set baselines for preferred models.
@ArizePhoenix: • Faster trace analysis: use natural-language filters, one-click chart zoom, and dedicated annotation columns. • Expand…
Arize Phoenix announces updates including faster trace analysis with natural-language filters and an expanded REST API for managing retention assignments and model providers.
@ArizePhoenix: Our favorite tools are the ones that have maximum customizability. Last week we added customizable charts, command K, a…
Arize Phoenix announces new customization features for its AI agent monitoring platform, including customizable charts, command K, recent searches, and custom column ordering.
@ArizePhoenix: Were buzzing with use-cases at @arizeai - so many optimizations to be made. Trace every judgement Jev makes with one li…
Arize Phoenix launches instrumentation support for tracing TypeSafe AI judgments, integrating with multiple developer tools and coding agents.
@ArizePhoenix: Customizable visualizations of your agent traces are here. Track cache hits, online eval degradations, tool call errors…
Arize Phoenix announces customizable visualizations for agent traces, enabling real-time tracking of cache hits, online eval degradations, and tool call errors in production.