On Tuesday, Google unveiled Gemini 2.5, a new family of AI reasoning models that pauses to “think” before answering a question.
To kick off the new family of models, Google is launching Gemini 2.5 Pro Experimental, a multimodal, reasoning AI model that the company claims is its most intelligent model yet. This model will be available on Tuesday in the company’s developer platform, Google AI Studio, as well as in the Gemini app for subscribers to the company’s $20-a-month AI plan, Gemini Advanced.
Moving forward, Google says all of its new AI models will have reasoning capabilities baked in.
Since OpenAI launched the first AI reasoning model in September 2024, o1, the tech industry has raced to match or exceed that model’s capabilities with their own. Today, Anthropic, DeepSeek, Google, and xAI all have AI reasoning models, which use extra computing power and time to fact-check and reason through problems before delivering an answer.
Reasoning techniques have helped AI models achieve new heights in math and coding tasks. Many in the tech world believe reasoning models will be a key component of AI agents, autonomous systems that can perform tasks largely sans human intervention. However, these models are also more expensive.
Google has experimented with AI reasoning models before, previously releasing a “thinking” version of Gemini in December. But Gemini 2.5 represents the company’s most serious attempt yet at besting OpenAI’s “o” series of models.
Google claims that Gemini 2.5 Pro outperforms its previous frontier AI models, and some of the leading competing AI models, on several benchmarks. Specifically, Google says it designed Gemini 2.5 to excel at creating visually compelling web apps and agentic coding applications.
On an evaluation measuring code editing, called Aider Polyglot, Google says Gemini 2.5 Pro scores 68.6%, outperforming top AI models from OpenAI, Anthropic, and Chinese AI lab DeepSeek.
However, on another test measuring software dev abilities, SWE-bench Verified, Gemini 2.5 Pro scores 63.8%, outperforming OpenAI’s o3-mini and DeepSeek’s R1, but underperforming Anthropic’s Claude 3.7 Sonnet, which scored 70.3%.
On Humanity’s Last Exam, a multimodal test consisting of thousands of crowdsourced questions relating to mathematics, humanities, and the natural sciences, Google says Gemini 2.5 Pro scores 18.8%, performing better than most rival flagship models.
To start, Google says Gemini 2.5 Pro is shipping with a 1 million token context window, which means the AI model can take in roughly 750,000 words in a single go. That’s longer than the entire “Lord of The Rings” book series. And soon, Gemini 2.5 Pro will support double the input length (2 million tokens).
Google didn’t publish API pricing for Gemini 2.5 Pro. The company says it’ll share more in the coming weeks.
Google just fired a warning shot in the AI subscription price wars
Google just made its budget AI subscription plan a lot more budget-friendly, bringing a price war that’s been brewing in emerging markets squarely to American consumers.
The company announced Monday that it is cutting the monthly price of Google AI Plus from $7.99 to $4.99 — while doubling the storage included at that tier, from 200 gigabytes to 400 gigabytes.
Vikas Kansal, product lead for Gemini AI subscriptions, said on X that the storage updates would roll out to users over the next several days.
Google AI Plus launched in January as the most affordable paid AI subscription in the U.S. market, aimed at individual users and students rather than enterprise customers. The new pricing makes that positioning even more explicit.
It includes a decent feature set, too, including video generation via Omni Flash; the creative studio Google Flow; and NotebookLM, Google’s AI research assistant. Users who need more — more features, higher usage limits — can step up to Google’s AI Pro or AI Ultra tiers.
But the more interesting story here isn’t about Google’s product lineup. Subscription pricing hasn’t been a key battleground among AI providers in the U.S. until now — and that shift has serious consequences for the broader market, suggests Chi-Hua Chien, co-founder and managing partner at Goodwater Capital, a consumer-focused venture firm in the Bay Area.
Chien sees Monday’s announcement as the next salvo in what he calls the commoditization era for AI infrastructure, pointing to Google’s structural advantages — vertical integration, massive distribution, the ability to bundle — as precisely the kind of force that’s likely to erode margins for purer-play AI providers over time.
The historical parallel he reaches for is instructive. “If you look at the web era, the infrastructure companies were Microsoft, Cisco, Oracle, Northern Telecom, Lucent, Akamai, Equinix,” he told TechCrunch. “A lot of those companies survived for a period of time but aren’t worth a lot today.” The reason, he said, is that during every big tech shift — from PC to web to mobile — the infrastructure players get “commoditized very aggressively because the end customer doesn’t think, ‘Ooh, are my bits moving on Cisco networking equipment?’ They’re just thinking, ‘How do I move my bits as cheaply as possible?’”
None of this is a surprise to the people building foundation models. They’ve always known that raw AI capability would eventually become a commodity, and that the real competition would play out at the application and distribution layer. What Chien is saying is that “eventually” is now.
“My prediction for a lot of these infrastructure companies — and when I say infrastructure, I mean an OpenAI or an Anthropic, or the backend components, energy, chips, hosting — there will be a period of time when these companies are valuable,” he said. “But over time, you will see them get increasingly commoditized.”
It’s certainly something that a bigger pool of investors will be pondering soon. Both OpenAI and Anthropic have filed confidentially to go public, and their ability to command premium valuations may soon be tested by exactly the kind of price competition Chien is describing.
That competition has been building for nearly a year in markets like India, one of the fastest-growing AI user bases in the world. OpenAI drew first blood there in August of last year, launching ChatGPT Go at roughly $4.60 a month — a fraction of its standard $20 Plus plan. Google followed in December with a sub-$5 AI Plus plan of its own for Indian users.
Monday’s announcement suggests the same logic that drove those emerging-market moves — undercut, bundle, and capture users before rivals do — has now crossed over to the U.S. market.
Anthropic, notably, hasn’t followed. Unlike OpenAI and Google, it has yet to introduce localized pricing for India or a budget tier anywhere, a move that may become harder to avoid as its rivals keep slashing prices.
