Anthropic Boosts Claude Code Performance by 3x, Cuts Response Lag to 1.33 Seconds
Key Summary
Anthropic has made significant improvements to its Claude Code, cutting response lag by nearly 3x to 1.33 seconds. The company has implemented two key changes: compressing conversation data and starting cloud sessions before users finish typing. This improvement has a ripple effect, impacting Claude's web and Cowork experiences as well as the API.
Improvements in Claude Code
Anthropic has made Claude Code noticeably less sluggish. First-token latency for local sessions fell from 4.07 seconds to 1.33 seconds between August and October 2026, an improvement of nearly 3x.
The fix was not a new model or an exotic breakthrough. It came from compressing conversation data and starting cloud sessions before users finish typing.
Where the seconds went
The update was announced on October 17, 2026, through the ClaudeDevs account. It covers several Claude products, with the headline gains in Claude Code.
The key metric is first-token p90 latency. First-token latency is how long you wait before the model starts producing any reply at all. The p90 label means 90% of requests came back faster than that figure.
For local Claude Code sessions, that p90 number dropped from 4.07 seconds to 1.33 seconds. Cloud sessions saw an even larger absolute cut, going from 16.99 seconds to 6 seconds, roughly 2.8x faster.
The two tricks behind the speedup
Anthropic started gzip-compressing those per-turn conversation payloads before sending them to the model. Gzip is a long-established compression format that shrinks data so it moves across the network faster. The benefit is biggest for long contexts, where developers often paste in large files, logs, and sprawling back-and-forth exchanges.
AI, tech, and the markets they move—
Anthropic has made Claude Code noticeably less sluggish. First-token latency for local sessions fell from 4.07 seconds to 1.33 seconds between August and October 2026, an improvement of nearly 3x.
The fix was not a new model or an exotic breakthrough. It came from compressing conversation data and starting cloud sessions before users finish typing.
What this means for developers and the AI coding market
For developers, latency is not a vanity metric. Coding assistants are used in rapid, iterative loops: ask, read, tweak, ask again. A few seconds saved per turn compounds across hundreds of turns in a working day.
The cloud improvement may matter most here. Going from 16.99 seconds to 6 seconds changes whether a developer stays in flow or drifts off to another tab while waiting.
By showing gains at the p90 level across local, cloud, web, Cowork and the API, Anthropic is signaling that it sees speed as a product feature across its whole lineup rather than a single tool.
Precedent & Market Context
Anthropic's projection of a $44 trillion US GDP by 2030 appears consistent with a strong positive outlook for the AI sector.
Anthropic's co-founder, Jack Clark, predicts AI could push US GDP to $44 trillion by 2030.
Anthropic has been working on improving its performance, with an internal sprint the previous month in which more than 3,000 updates produced similar performance improvements across various Claude products.