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  3. 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

    Matched fieldsTitle、Summary、Body

    #hot-signal#Model releases#English text is being prepared.#Reasoning
  4. 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.