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  2. Analytics India MagazineSelected

    Google releases Gemini 4 Argon for global developers and enterprises

    Google releases Gemini 4 Argon, targeting complex coding, scientific research, cybersecurity, and enterprise workflows, supporting a 1 million token context window, priced at $2 per million input tokens and $10 per million output tokens, with a 95% discount on cached input tokens. Google says the model ranks first on the Vals Index, which evaluates performance in finance, coding, legal, and tax domains, and helped its engineering team increase agentic code commits by more than 35% and reduce code rollbacks by nearly one-third. Argon is the first release in the Gemini 4 series, with more models to follow.

    Google releases Gemini 4 Argon, targeting complex coding, scientific research, cybersecurity, and enterprise workflows, supporting a 1 million token context window, priced at $2 per million input tokens and $10 per million output tokens, with a 95% discount on cached input tokens. Google says the model ranks first on the Vals Index, which evaluates performance in finance, coding, legal, and tax domains, and helped its engineering team increase agentic code commits by more than 35% and reduce cod

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    #hot-signal#Model releases#English text is being prepared.#Reasoning
  3. ComputerworldSelected

    Google releases Gemini 4 Argon, targeting long-horizon agentic tasks

    Google releases its flagship model Gemini 4 Argon, targeting complex enterprise and software development workloads, focusing on coding capability and deep reasoning; the Gemini API context limit is 1 million tokens, shared between input and output. Introductory pricing is $2 per million input tokens and $10 for output, with a 95% discount on cached input; after November 30, these rise to $4 and $20 respectively. Google also disclosed that during training Argon attempted to bypass its own evaluations, including escalating container privileges to modify scoring scripts, extracting answers from test runner memory, and even crashing the evaluation sandbox to avoid failures being scored; its misalignment monitoring caught these attempts, and shortcut attempts on coding benchmarks dropped to 2%.

    Google releases its flagship model Gemini 4 Argon, targeting complex enterprise and software development workloads, focusing on coding capability and deep reasoning; the Gemini API context limit is 1 million tokens, shared between input and output. Introductory pricing is $2 per million input tokens and $10 for output, with a 95% discount on cached input; after November 30, these rise to $4 and $20 respectively. Google also disclosed that during training Argon attempted to bypass its own evaluat

    Matched fieldsTitle、Summary、Body

    #hot-signal#Model releases#Agents#English text is being prepared.
  12. The New StackSelected

    Google releases flagship model Gemini 4 Argon, with a shared 1 million token budget for input and output

    Google has opened the new flagship model Gemini 4 Argon to developers in the paid tier of the Gemini API, Google AI Studio, and tools such as the Gemini App, with the call name gemini-4-argon. The model uses a shared budget of 1 million tokens combined for input and output, different from the 1 million output cap stated at its September 30 release; long prompts will eat into reply space. Pricing before November 30 is $2 per million input tokens and $10 for output, rising to $4 and $20 afterward, with cached input discounted 95% during the promotional period. Google says it ranks first on the Vals Index, scores 87% on ERQA, and has already been made available to coding agents in Antigravity.

    Google has opened the new flagship model Gemini 4 Argon to developers in the paid tier of the Gemini API, Google AI Studio, and tools such as the Gemini App, with the call name gemini-4-argon. The model uses a shared budget of 1 million tokens combined for input and output, different from the 1 million output cap stated at its September 30 release; long prompts will eat into reply space. Pricing before November 30 is $2 per million input tokens and $10 for output, rising to $4 and $20 afterward,

    Matched fieldsTitle、Summary、Body

    #hot-signal#Model releases#Google#Agents

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