For Google fans, June was supposed to be a month of major announcements. Instead, we were met with ambiguity once again. According to information from current technology analyses, the release of Gemini 3.5 Pro is being moved to July 2026. Why would a giant like Google risk losing momentum at a time when the competition is constantly picking up pace? The answer lies in the ambitious parameters this model demands.
Why the delay is necessary: The battle for quality vs. speed
A delay isn't always a sign of failure; in the case of cutting-edge language models, it's often about ensuring safety and stability. Based on indications, Google is focusing on three key areas that must be perfect before the model reaches the hands of the general public:
1. Agentic AI capabilities
Today's chatbots are primarily interactive tools. The future belongs to agents — systems that not only answer questions but can independently plan and execute steps to achieve a goal (e.g., planning an entire software architecture and then creating basic modules). Google must ensure that the model doesn't "get lost" during these multi-step tasks and maintains logical coherence from start to finish.
2. Long-horizon reasoning
The model's ability to solve complex problems requiring multiple logical steps is critical. If the model makes an error in the second step out of ten, the entire result is unusable. Google is now fine-tuning the model's ability to maintain a high level of logical accuracy even when solving highly complex, large-scale problems.
3. Efficiency and token optimization
When working with vast amounts of data (including lines of code), computational costs rise dramatically. Previous models, such as the Flash version, showed that excessively rapid token "burning" can be economically unsustainable for businesses. Gemini 3.5 Pro must find the ideal balance between depth of analysis and cost per query.
Benchmarks and comparisons: Where does Google stand?
To understand what's expected, we need to look at the current competition. Gemini 3.5 Pro aims to surpass not only previous versions but also the market leaders:
- Gemini 3.5 Pro vs. GPT-o1/GPT-5: OpenAI currently dominates the "reasoning" space. However, Google holds the advantage of integration with the Google Cloud and Workspace ecosystem, which can be crucial for businesses.
- Gemini 3.5 Pro vs. Claude 3.5/4: Anthropic is known for its ability to write highly natural and "human-like" code. Gemini, however, is striving to win in the context window category.
The key parameter that Google confirms is a context window of 2 million tokens. To put that into perspective: this allows the model to "read" entire thousand-page documentation sets or entire code repositories at once. While competing models often require splitting data into smaller chunks (RAG — Retrieval-Augmented Generation), Gemini 3.5 Pro can work with the entire context in a single batch, dramatically reducing the risk of hallucinations.
Practical impact for the Czech market and developers
What does this mean for you? If you're a software house in Prague or Brno, or working as a freelancer, Gemini 3.5 Pro could be a game-changing tool for coding automation. The model's ability to understand an entire project at once means it can help you refactor old legacy code, which is a common challenge in the Czech IT sector.
Availability and the Czech language: Google has traditionally offered very good support for Czech. It is highly likely that Gemini 3.5 Pro will be fully functional in Czech — not only for chatting but also for analyzing Czech documents. From a regulatory standpoint, it's important to mention the EU AI Act. Google must ensure its models comply with strict European safety and transparency standards, which may be one of the factors prolonging testing in Europe.
Pricing and access
The model is currently available only to select enterprise customers through the Vertex AI platform as part of a preview program. The following structure is expected for regular users:
- Gemini Advanced (subscription): Likely around $20/month (approximately CZK 470), which is the standard price for premium AI assistants.
- Enterprise/Developer: Pay-per-token usage via Google Cloud, allowing businesses to scale costs based on actual usage.
Conclusion
The delay of Gemini 3.5 Pro is not a sign of weakness, but rather an effort to push the boundaries between a simple chatbot and a true autonomous agent. For the Czech tech scene, this means waiting for a tool that could radically increase development efficiency — if Google succeeds in solving stability at extremely long contexts.
Will Gemini 3.5 Pro work in Czech as well as in English?
Google has historically invested significant resources in localization. Although the latest models are primarily trained on English, the multilingual processing capabilities of the Gemini family are top-tier, and Czech will be fully supported, especially for text analysis.
Can I try the model for free right now?
You can use the standard models for free through the public Gemini interface (gemini.google.com). For Gemini 3.5 Pro, however, you currently need access via Vertex AI or you'll need to wait for integration into the paid Gemini Advanced tier.
What's the difference between a context window and the model's memory?
The context window determines how much information the model can "see" and process at once (e.g., your entire code project). Memory (or training data) is what the model already "knows" from the training process. A large context window allows the model to work with your current data without needing it to be pre-learned.
