Carl Franzen

Anthropic calls Haiku its fastest model at standard speeds, while acknowledging that Opus in Fast Mode runs faster. It does not supply a tokens-per-second figure in the materials reviewed for this article.

For an enterprise early in robotics, a useful starting point would be one bounded workflow, such as packing a particular product or assembling a specific part.

All models receive one fixed prompt. The team does not specifically instruct them to imitate human authors or suppress known tells.

The company is positioning Argon around three areas where enterprises are already spending: software development, professional knowledge work and cybersecurity operations.

For enterprises, ChatGPT Space could turn Dots from individual assistants into participants in shared team workflows. OpenAI describes Space as a shared environment where teammates, ChatGPT and a Dot can work from the same project knowledge.

Anthropic says that on several evaluations, Sonnet 5.5 running at Low or Medium effort can surpass Sonnet 5’s best score at roughly one-tenth the cost per task.

The company says it trained task-specific FLUX 3 Action policies to fly drones in real life and even successfully beat the hit computer game Doom with no in-game deaths.

At Luna’s prices, routine extraction and summarization can be pushed toward a much cheaper tier. Sol targets recurring coding and agent work at Sonnet-class token pricing. Astra remains available for the hardest jobs.

Anthropic reports that Opus 5.5 performs better than recent Claude models across nearly every measure in its roughly 2,000-scenario automated behavioral audit.

For enterprise teams, the larger lesson extends beyond one vulnerable image decoder. AI agents are increasingly being given credentials and connectors that span source code, communications and corporate data.