Google's Gemini 3.5 Pro delayed – fails to meet internal targets
The launch of Google's flagship model Gemini 3.5 Pro has been delayed after failing to reach internal performance benchmarks, particularly in coding capabilities.

What happened?
Google's launch of the AI model Gemini 3.5 Pro is several months late. The delay is attributed to the company's efforts to enhance the model's capacity. Specifically, the model has fallen short of internal targets, primarily within the coding domain, according to Bloomberg sources.
Key facts
| Modell | Gemini 3.5 Pro |
|---|---|
| Status | Lansering försenad |
| Förseningsorsak | Når inte interna mål (särskilt kodning) |
| Företag | Alphabet Inc. (Google) |
”Alphabet Inc.’s Google is months behind schedule on delivering Gemini 3.5 Pro, its most powerful flagship AI model, because the company has been taking time to try to improve its capabilities, particularly in coding, according_to people familiar with the matter.”
Why it matters
The delay indicates that the development of advanced AI models remains complex and that internal quality standards are being prioritised. Performance and reliability, especially in programming tasks, are critical for future applications and user adoption.
Who is affected?
Developers awaiting Gemini 3.5 Pro, companies planning to integrate advanced AI into their solutions, and Alphabet Inc. shareholders are affected. Users of Google's AI services may also be indirectly impacted by the delayed release.
What else you should know
The delay highlights the challenges involved in iteratively improving powerful AI models to meet high standards for performance and functionality.
Quick answers about this story
Vad har hänt?
När hände det?
Varför spelar det roll?
Vilka bolag berörs?
The link opens in a new window and leads to the publisher's own site.
Källan har spårats automatiskt från utgivaren via Aheadlines signalkedja.
AI-verktyg i artikeln
Topics
Get similar news straight to your inbox
The reader's room
Send in a question or an addition. The newsroom reads everything before it's published and replies when relevant. No AI-generated text – just people.
Sign in to submit a comment or question.
Read the article through your role
- Assess technical risk: model choice, vendor lock-in, data flow and running cost.
- Update the architecture doc if new APIs or regulations touch production.
- Ensure observability + rollback plan before rolling out to production.
Generated angle — not editorial analysis of "Google's Gemini 3.5 Pro delayed – fails to meet internal tar"