Expected for June 2026, Google’s powerful Gemini 3.5 Pro artificial intelligence model is seriously behind schedule. Internally, his shortcomings in computer programming are worrying.
It is a delay in ignition which is starting to cost the Mountain View firm dearly, to the point of causing Alphabet’s stock to stumble by 4% on the stock market. Announced with great fanfare last May during the annual Google I/O conference, the most powerful version of its artificial intelligence model, Gemini 3.5 Pro, was logically due to arrive immediately, during June 2026. Its role was to support the lighter version called Gemini 3.5 Flash. Several months later, Google’s flagship is still conspicuous by its absence, and the reasons for this blockage have just been highlighted by an investigation by Bloomberg.
Computer code, the Achilles heel of AI
If Google refuses for the moment to advance any official release date, contenting itself with affirming through the voice of its spokespersons questioned by CNBC Although the model is still being tested with certain partners, the internal reality seems much more tense. The American company’s engineers and researchers are said to be particularly disappointed with Gemini 3.5 Pro’s programming and code generation capabilities. Despite a massive update of training data at the end of June, laboratory results remain stubbornly below the requirements set by management.
This technical gap comes at the worst time for the search giant. Computer code has indeed become the crux of the matter and the main selling point for monetizing AI with developers and businesses. While Google is slipping, the competition is advancing at a breakneck pace. OpenAI has just launched its formidable GPT-5.6 Sol model, claiming superior technical efficiency on coding tasks, while Anthropic seduces professionals with its powerful Fable 5. Even Meta entered the dance last week with Muse Spark 1.1, presented by its teams as the most robust open-source tool for autonomous development work.
Administrative burden that weighs on innovation
Beyond simple technical obstacles, this delay would also highlight chronic organizational problems at Alphabet. The development of the Gemini ecosystem today involves a multitude of teams and decision-makers, each seeking to integrate AI into their own division, whether it is YouTube, Maps or the search engine. This multiplication of hierarchical validations considerably slows down the rate of release of updates.
Some internal voices also believe that Gemini’s main objective should not be fierce competition on programming intended for experts, but rather the direct improvement of general public functions, such as the famous AI Overviews integrated into search results. While waiting for Google to decide on its strategy and manage to raise its model to the level of its rivals, the company is asking its users to be patient with the current version 3.1.
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