Google on Thursday rolled out a revamped version of its Gemini Deep Research agent, rebuilding the tool on top of Gemini 3 Pro, the company’s latest flagship foundation model.
The new system is designed not only to generate long-form research reports, but also to function as an embeddable research engine that other developers can plug directly into their own applications.
The timing was not lost on anyone in the industry. What once looked like a broad field of AI competitors is becoming narrowed into a head-to-head sprint between two giants that now announce upgrades within the same news cycle, each determined to stay a step ahead in the escalating race for model dominance.
Google’s upgraded Deep Research system is no longer just a tool for generating polished research reports. It has broadened into a programmable research agent suited for large-scale information synthesis, built to survive massive context loads and long reasoning cycles that would normally push an LLM into error territory.
The company is positioning it as a backbone for due diligence review, drug toxicity evaluation, and other high-precision analytical tasks. The major engineering shift was the introduction of Google’s new Interactions API — a feature aimed at letting developers embed Deep Research-grade capabilities into their own products and control the agent layer more directly.
Google also disclosed plans to integrate Deep Research into a series of its core services, including Search, Finance, the Gemini app, and NotebookLM. It is edging toward an internet where people no longer hunt for information themselves; they dispatch an agent trained to do it for them. Google leaned heavily on the claim that Gemini 3 Pro is its “most factual” model so far, tuned to lower hallucination rates in long-chain reasoning tasks where a single incorrect step can ruin the entire output.
To back its performance claims, Google introduced a new benchmark called DeepSearchQA, intended to test how well an agent handles complex, multi-step information missions. It was released as open source. The company also tested the system on Humanity’s Last Exam, a notoriously difficult general-knowledge benchmark filled with obscure tasks, and on BrowserComp, which evaluates an AI agent’s ability to carry out browser-based operations.
In addition to the widely-praised Gemini 3, Deep Research topped the leaderboard on Google’s own benchmark and on Humanity’s. But OpenAI’s ChatGPT 5 Pro landed close behind in both tests and overtook Google on BrowserComp. Even those results barely had time to settle. Hours later, OpenAI announced GPT-5.2, which the company said outperforms rivals — including Google — across a wide suite of standard benchmarks.
This back-to-back rollout marked another escalation in a rivalry that has grown unusually public. The industry now watches releases from both companies like heavyweight rounds. Each upgrade arrives with the sense of a reply to the other.
Google introduced a package that pushes its agentic vision further, giving developers a programmable research companion and moving the company closer to agent-based search. OpenAI countered with a model built to strengthen its leadership in reasoning, speed, and multimodal performance.
The speed of these releases also signals how aggressively both companies are trying to define the next phase of AI development. The focus is shifting from raw model power to advanced agents that can plan, browse, run tools, complete tasks over long stretches, and handle increasingly complex workloads with minimal supervision. Whoever builds the most reliable and scalable agent layer stands to redefine how people use software, how information moves across the web, and how organizations make decisions.
For now, Google seems to be pushing deeper into agentic research systems integrated across its own ecosystem, while OpenAI continues to refine its core model lineup and deploy it across consumer and enterprise channels. Each announcement seems to trigger the next. Each benchmark update sets off another. And as these systems continue to evolve in public view, the industry’s center of gravity keeps shifting toward a true duel for AI supremacy.






