Stripe said on Aug. 19, 2026 that it had reached an agreement to acquire OpenRouter in what would be the company’s largest acquisition to date. The final price was not disclosed, though media reports placed the deal at more than $7 billion to $8 billion, with The New York Times citing roughly $7.5 billion. That figure stands in sharp contrast to OpenRouter’s roughly $1.3 billion Series B valuation just 83 days earlier, implying a near sixfold repricing in less than three months. The PANews analysis argues that OpenRouter has already proved one thing at scale: inference demand can be aggregated across hundreds of models and dozens of compute providers. The company says it handles more than 400 trillion monthly tokens, serves more than 10 million global users, connects 80-plus suppliers and 500-plus models, and supports more than 250,000 apps reaching over 4.2 million end users. Yet the same OpenAI-compatible standard that helped OpenRouter grow also keeps switching costs extremely low, since developers can often leave by changing a base URL and API key. In that framing, Stripe is not simply buying an API gateway. It is betting that OpenRouter can evolve from a replaceable middleware layer into a control point that links model routing, telemetry, agent identity, budgeting, metering and settlement. Whether that transition happens is presented as the central question behind the deal.

Meta has officially made its SAM 3.1 visual segmentation model available through Model API, giving developers a hosted way to run object segmentation on images and videos without managing model weights, GPUs, or deployment infrastructure themselves. After submitting an image or video and entering a text prompt such as "red bicycle," users can identify the matching object and receive both bounding boxes and pixel-level masks. The API also supports tracking the same object through video, which Meta says can be used for tasks such as automatic blurring and visual effects. Meta had already released an open-weight version of SAM 3.1 in March this year. Compared with SAM 3, the biggest change in SAM 3.1 is Object Multiplex. Instead of handling multiple targets one by one, the model can now process up to 16 targets at the same time. In Meta’s tests, a single H100 increased multi-object video processing speed from 16 frames per second to 32 frames per second. When tracking 128 objects, performance was about 7 times faster than SAM 3. Meta said image segmentation is priced at $2.5 per 1,000 images, while video costs $0.2 per 1,000 frames. The API can also be accessed through the OpenAI SDK, though the hosted version currently accepts only text prompts. The open-weight version still supports visual prompts such as boxes and points.

Google has released the 1.0 version of its Kotlin generative AI SDK, designed to enhance mobile AI integration. The toolkit supports on-device generative AI, improving development efficiency and strengthening privacy protection.

A new report cited by ChainCatcher says Google could roll out Gemini 3.7 Flash as soon as today, with API pricing potentially dropping to $0.75 per million input tokens and $3.75 per million output tokens. That would be a sharp reduction from the current standard pricing for Gemini 3.6 Flash, which stands at $1.50 for input and $7.50 for output per million tokens. If the leaked pricing is accurate, the new model would come in at roughly half the current rate. The report also notes that speculation around Gemini 3.7 Flash has been building for some time. Google’s official Python GenAI SDK briefly included a reference to `gemini-3.7-flash`, before the related pull request was renamed to "internal" and then closed. Separately, SemiAnalysis said last week that Google had internally canceled Gemini 3.5 Pro, previously seen as a flagship model, and shifted the team toward a larger Gemini 4 effort. According to leo, he has heard the same internally.

Neura has closed a strategic funding round to advance emotional AI agents with persistent memory, user-owned identity, and an on-chain memory ledger designed for portability and privacy.

Circle said its Agent Stack starter kit is now open source, giving developers a way to add wallet support, USDC payments, and onchain actions to AI agents. The toolkit is designed to work with several widely used agent and AI development frameworks, including OpenAI Agents SDK, Claude Agent SDK, LangChain Deep Agents, Mastra, Vercel AI SDK, and Google AI ADK. The announcement points to a developer-focused release aimed at making crypto-enabled agent functions easier to integrate across existing AI stacks. Circle did not disclose additional technical details in the source post beyond the supported frameworks and core capabilities.

Crypto.com has released a beta AI Agent SDK that lets developers trigger blockchain actions with natural language commands, aiming to simplify wallet creation, transfers, swaps, and broader Web3 application development.

Crypto.com has released a beta AI Agent SDK that lets developers trigger wallet creation, transfers, and token swaps through natural language, aiming to simplify Web3 product development and user interactions.