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Artificial Analysis Makes Time per Task Headline

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Artificial Analysis Makes Time per Task Headline
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// 1h agoPRODUCT UPDATE

Artificial Analysis Makes Time per Task Headline

Artificial Analysis replaced tokens per second with Time per Task as its headline performance metric, incorporating full-request latency and agentic workloads. Claude Opus 5.5 streams over twice as fast as GPT-6 Astra yet takes roughly seven minutes longer to finish its benchmark tasks because it generates far more tokens.

// ANALYSIS

This is a necessary correction: streaming speed measures how quickly a model types, not how quickly it completes useful work.

  • –Opus reaches roughly 112 tokens per second versus Astra’s 47, but takes 25.8 minutes per task versus 18.4 minutes.
  • –Astra’s advantage comes from generating dramatically fewer tokens, highlighting the cost of verbosity and extended reasoning.
  • –The new metric better matches coding agents and knowledge-work systems, where latency, reasoning length, and multi-turn execution compound.
  • –It remains a derived benchmark estimate rather than a stopwatch measurement of every production workflow.
  • –Developers should compare models at their intended API effort level, since default and maximum effort can produce radically different speed, cost, and quality tradeoffs.
// TAGS
artificial-analysisbenchmarkevaluationinferencestreamingobservability

DISCOVERED

1h ago

2026-11-04

PUBLISHED

2h ago

2026-11-04

RELEVANCE

8/ 10

AUTHOR

AdamHoltererer