On Monday, June 22, Google started rolling out Gemini 2.5 Pro with Deep Think, and called it the most capable model it has ever released (Google). The early read from the people watching benchmarks is blunt: this may be the strongest publicly available model from any lab right now (Medium — AI Update, June 22).
I’ve been around this space long enough to be skeptical of "best ever" headlines. Every lab says it every quarter. So let me separate what’s real from what’s noise, and then tell you what I’d actually do about it.
What actually shipped
Two things matter here, and they’re different.
First, Deep Think mode. Instead of answering instantly, the model takes extra time to break a problem apart, run several reasoning paths in parallel, and check its own logic before it answers (Google). This is Google’s version of the "thinking" approach that OpenAI and Anthropic shipped first. It’s slower per answer. It’s also better on the hard stuff — math, science, multi-step reasoning, and code.
Second, the context window. Gemini 2.5 Pro carries a 2-million-token window, which means it can ingest an entire codebase, a full book, hours of video, or months of conversation history in one session (Medium — AI Update, June 22). That’s not a benchmark flex. That’s a workflow change. If you’ve ever had to chop a big document into pieces to fit it into a model, you know exactly why this is a big deal.
The part the leaderboard doesn’t show
Here’s what’s easy to miss in the model-of-the-week cycle: the competitive picture is shifting underneath all of this.
By one 2026 market read, ChatGPT’s share of the AI assistant market has slipped to 46.4%, while Gemini has climbed to 27.7% and Claude sits around 10.3% (Build Fast with AI). ChatGPT is still the giant. But Google has gone from "the one that was behind" to a genuine number two, and it did it by bundling Gemini into products people already pay for — Workspace, Android, Search.
That’s the strategic story. Google doesn’t need to win on benchmarks alone. It needs to be good enough and already inside the tools you use. With Deep Think, it’s now arguably both.
What this means for you — independent operators and SMBs
If you run your own business or work for yourself, here’s my honest take: don’t switch your whole stack because of one launch.
A new top model is exciting. It is not a reason to rip out tools that already work for you. The right move is to test, not to migrate. If you’re already in Google Workspace, Deep Think is the lowest-friction upgrade you’ll get all year, because it’s showing up where your email and docs already live. Try it on something hard — a messy contract, a tangled spreadsheet, a research task you’ve been putting off — and see if the slower, more careful answers are worth the wait.
If you’re not in the Google ecosystem, there’s no urgency. The model you’re using today did not get worse on Monday.
What this means for you — enterprise IT
This is where it gets more interesting, and more careful.
A 2-million-token window plus stronger reasoning is genuinely useful for the work IT actually does: reviewing large codebases, reasoning over long incident histories, parsing sprawling policy and compliance documents. If your shop is standardized on Google, this is a real capability bump you didn’t have a week ago.
But I’d slow down on two fronts. First, "most capable model" benchmarks rarely survive contact with your actual data and your actual guardrails. Run your own evals before you tell leadership anything. Second — and I say this every time — a bigger, more autonomous model is a bigger surface to govern. More context ingested means more sensitive data in the prompt path. Pair any rollout with a clear answer to: where does this data go, who can see the outputs, and what is it allowed to act on.
My take
The headline that matters isn’t "Google made the best model." It’s "the lead now changes hands every few weeks, and the labs are this close to each other." That’s good for you. Competition like this means better tools at lower prices, and it means you should never lock yourself into a single vendor’s roadmap as if it’s permanent.
I’ve personally only run agentic work daily through Claude Cowork and Microsoft Copilot Cowork, so I’m not going to pretend I’ve put Deep Think through its paces yet. What I will say is that the smart posture right now is the same one it’s been all year: stay tool-agnostic, keep your data portable, and let the labs race. You benefit either way.
Don’t chase the leaderboard. Build a workflow that can swap the engine when a better one shows up — because next month, it will.
News commentary by Brad Rowland — IT Infrastructure and Operations leader, automation builder, and AI implementer. Sources are linked inline.
![Head-to-Head: Claude Cowork vs Microsoft Copilot Cowork — Where Each One Actually Wins [Updated June 2026]](https://aitechtoolkit.com/wp-content/plugins/contextual-related-posts/default.png "Head-to-Head: Claude Cowork vs Microsoft Copilot Cowork — Where Each One Actually Wins [Updated June 2026]")
