Models & Releases

Google AI Just Released Gemini 3.7 Flash: A Coding and Agent Model at $0.75/1M Input Tokens

Google has released Gemini 3.7 Flash, the newest model in its Flash tier, three weeks after Gemini 3.6 Flash. The model card describes it as a refinement of 3.6 Flash with algorithmic improvements to the core reasoning foundation — not a new pretraining run. It accepts text, images, audio, and video across a 1M-token context window, returns up to 64K output tokens, and supports customizable thinking configurations that trade quality against cost and latency. The knowledge cutoff stays at March

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Google released Gemini 3.7 Flash, an AI model refinement designed for coding, document work, and web development that accepts text, images, audio, and video inputs. The model's main competitive advantage is price: it costs $0.75 per 1 million input tokens until the end of 2026, roughly half the cost of its predecessor and a third the cost of competing models from other companies. Performance improvements are concentrated in software engineering tasks, where it shows measurable gains on coding benchmarks, though it trails on some computer-use and terminal tasks. The model is available only through API and cloud platforms with no open-source weights, making it unsuitable for organizations requiring self-hosted or air-gapped deployments.

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Gemini 4 Carbon is now available

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Google Launches Gemini Decisions API With Gemini Decision 1 at $0.10/M Tokens

Google has launched the Gemini Decisions API, powered by a new model, Gemini Decision 1 (gemini-decision-1). The Gemini Decisions API does not generate text. It scores up to 1,000 typed questions against one shared input and returns calibrated probabilities. For developers, this targets the small branching calls inside agents: routing, policy checks, tool selection and grading. Google prices it at $0.10 per 1M input tokens, with zero output tokens billed. TL;DR Size: Context is 262,144 t

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Introducing AlphaProof Code: a breakthrough in verifying complex software at depth

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