Google Antigravity is our agentic development platform, allowing anyone to build in the agent-first era.
Antigravity is Google AI Studio for code — a browser-based AI coding environment from Google that lets you build, run, and iterate on software with Gemini AI. It brings Google AI capabilities directly into a development workflow.
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Four AI agents running on Google's Gemini 4 Argon beat Minecraft, including the Ender Dragon, with no human input. The run took 27 hours and 14 minutes and cost $1,620 at the model's standard 2027 pricing.
Google DeepMind's Gemini 4 Argon scored 97.5% on ARC-AGI-3 at a cost of $4,800 using the Provider Adapter Harness, according to ARC Prize. Under the Standard Harness it falls to 49.8%, and Epoch AI places it eighth on its Math ECI and sixth on its SWE ECI.
Google DeepMind researchers used the Antigravity agentic platform and the ProtNLM function-prediction model to flag a previously uncharacterized, 97-amino-acid bacteriocin candidate in UniProt. The lead is predicted to be active against respiratory tract pathogens but has not been experimentally confirmed. Google also introduced a Biomolecular Structure Viewer inside Antigravity.
GPT-6-Astra, running in OpenAI's Codex, solved 49 of 50 problems (98%) on TheoPhysEval, a new benchmark of unpublished theoretical physics research problems, at just under $116 for the full run. Anthropic's Opus 5.5 in Claude Code placed second at 92%. The authors say the agents now match specialists on concrete calculations but lack research "taste."
Google DeepMind began a broad rollout of Gemini 4 Argon on Oct 13, 2026 and published details of its safety stack. The company claims the model solved all 12 end-to-end simulated cyberattack scenarios, up from five in the prior generation, and cut shortcut attempts on coding benchmarks to 2%.
Google DeepMind says Gemini 4 Argon scores 87% on the Embodied Reasoning (ERQA) benchmark using pure reasoning, ahead of every other frontier model. A new robotics post demonstrates robot control, Real2Sim reconstruction, physical understanding, and self-improvement workflows. Pricing, context window, and availability were not disclosed.
Google DeepMind has released Gemini 4 Argon, its latest frontier model, globally via the API at an introductory $2 per 1M input tokens and $10 per 1M output tokens. Google claims it ranks #1 on the Vals Index. Context window, parameter count and training cutoff were not disclosed in the announcement.
Google DeepMind's AlphaProof Nexus solved nine of 353 open Erdős problems and proved 44 OEIS conjectures, according to a study published in Science. The system pairs Gemini 3.1 Pro with the Lean proof assistant, and the work went through peer review, unlike other recent AI-math releases.