Google DeepMind Details Gemini Deep Think Progress in Math and Science Research

Announcement Overview

Google DeepMind published a detailed research update on February 11, 2026 about Gemini Deep Think as a scientific assistant for mathematics, physics, and computer science. The company says the work was carried out with expert researchers and backed by two recent papers (ArXiv: 2602.10177 and 2602.03837).

The post positions this as a continuation of prior milestone claims: an advanced Gemini Deep Think version reaching Gold-medal standard at IMO in summer 2025 and similar performance later at ICPC world finals, then moving from contest-style tasks toward open-ended research workflows.

Agent Design and Evaluation Signals

DeepMind introduced a math research agent internally codenamed Aletheia. The workflow uses iterative generation, verification, and revision, with a natural-language verifier identifying flaws in candidate proofs. A notable design choice is explicit failure admission when no reliable solution is found, intended to reduce wasted researcher time.

Reported performance up to 90% on IMO-ProofBench Advanced as inference-time compute scales

Use of search and browsing inside the workflow to reduce citation and calculation errors

Claims of progress across 18 expert-collaboration research problems spanning multiple fields

Research and Publication Context

The company describes outcomes across theoretical CS, optimization, economics, and physics, with a mix of conference and journal trajectories. The post also emphasizes taxonomy and documentation standards for AI-assisted research contributions, and explicitly states it does not claim “landmark breakthrough” levels in its own highest categories at this stage.

Why It Matters

This update is important because it reframes LLM competition from benchmark demos to scientific workflow integration with verifiers, iterative reasoning, and human expert oversight. The practical question now is external validation: how many of these results replicate broadly and hold up under independent peer review. Even with that caveat, DeepMind’s report is a high-signal indicator of where frontier AI labs are investing in 2026.

Source: Google DeepMind blog