Insider Brief
- Google has made Gemini 4 Argon broadly available to developers, enterprises and consumers, expanding the model beyond its initial early-access rollout.
- Argon is available through the paid Gemini API, AI Studio, the Gemini platform, Google Antigravity and select Gemini app and AI Mode subscriptions, with introductory pricing of $2 per million input tokens and $10 per million output tokens.
- Google said the model supports a 1 million-token unified input-output context window, while researchers can apply for six months of high-tier Antigravity access and cybersecurity professionals can seek access through the Fairwind Program.
Google has launched Gemini 4 Argon for developers, enterprises and consumers, setting introductory API pricing for the frontier model as it moves beyond the early-access and demonstration phase.
According to Google, Argon is now available globally through the paid Gemini API in AI Studio and the Gemini platform, as well as through Google Antigravity for Google AI Ultra subscribers. Google AI Ultra and Pro subscribers can also access the model through the Gemini app and AI Mode in Search.
Google priced Gemini 4 Argon at $2 per million input tokens and $10 per million output tokens, with cached input tokens discounted by 95%. Google said the model supports a unified input-output context window of up to 1 million tokens through the Gemini API, aimed at longer-running scientific, coding and agentic tasks.
The company is also expanding access for specialized users. Researchers can apply for six months of the highest Google Antigravity usage tier at no charge, subject to eligibility and capacity, while cybersecurity professionals can apply to Google’s Fairwind Program for access to Argon under separate security arrangements.
Coding
Google said Argon ranks first on the Vals Index, a benchmark covering professional work in areas including finance, coding, legal and tax. Internally, Google engineers using Argon through Antigravity increased agent-generated code submissions by more than 35% while reducing code rollbacks by nearly one-third, according to the company.
The model has also been used to optimize existing software, according to Google. Argon helped restructure portions of Chromium’s 40 million-line codebase and reduced work that would have taken months to weeks. On Google’s open-source Agent Development Kit, Argon-generated changes cut in-memory session preparation time by 40% in long sessions and improved cold-import performance by 21%.
Research
Google also pointed out Argon’s capabilities for scientific and engineering research. The company said the model helped improve quantum error-correction software, contributed to work on nuclear-fusion mathematics and assisted with rare-disease genome analysis and enzyme design. Also, Google is offering 10,000 scientists access to the highest usage tier of Antigravity for six months, subject to eligibility and capacity.
Robotics
Robotics is another area where Argon’s use was highlighted by Google. The company noted that Argon scored 87% on its Embodied Reasoning benchmark, which measures a model’s ability to reason about physical and spatial problems in 3D environments. In an internal test, Argon watched video of a person playing cornhole, mapped the scene, calculated required body movements and generated simulation code. The resulting behavior was transferred to Apptronik’s Apollo humanoid, which made seven consecutive shots in a real-world trial, according to Google.
Google described the process as a “Video-to-Sim-to-Real” pipeline meant to reduce the time required to create robot-training simulations from weeks to hours.
Added Safeguards
The company also introduced additional safeguards around agent behavior, prompt injection and potentially harmful requests. Argon supports a 1 million-token unified input-output limit through the Gemini API, allowing it to work across long-running coding, research and agentic tasks.