Continue Integrations

Pixtral Large is a comprehensive multimodal model developed by Mistral AI, boasting an impressive 124 billion parameters that build upon their earlier Mistral Large 2 framework. The architecture consists of a 123-billion-parameter multimodal decoder paired with a 1-billion-parameter vision encoder, which empowers the model to adeptly interpret diverse content such as documents, graphs, and natural images while maintaining excellent text understanding. Furthermore, Pixtral Large can accommodate a substantial context window of 128,000 tokens, enabling it to process at least 30 high-definition images simultaneously with impressive efficiency. Its performance has been validated through exceptional results in benchmarks like MathVista, DocVQA, and VQAv2, surpassing competitors like GPT-4o and Gemini-1.5 Pro. The model is made available for research and educational use under the Mistral Research License, while also offering a separate Mistral Commercial License for businesses. This dual licensing approach enhances its appeal, making Pixtral Large not only a powerful asset for academic research but also a significant contributor to advancements in commercial applications. As a result, the model stands out as a multifaceted tool capable of driving innovation across various fields.

The Meta Model API serves as a groundbreaking developer interface that leverages Muse Spark 1.1, Meta's cutting-edge multimodal reasoning model specifically designed for agentic applications such as programming, tool use, and extensive computer interactions. Currently in its public preview phase, this API allows developers to easily integrate Muse Spark 1.1 through an OpenAI-compatible package, ensuring a smooth transition for current clients while preserving the existing code structure and facilitating straightforward adjustments to the muse-spark-1.1 model. This model is particularly adept at performing personal agentic tasks, enabling effective planning and coordination across a range of external applications and services, in addition to its ability to adapt to new native tools, MCP servers, and customized skills. When functioning as a primary agent, it can gather contextual information, formulate plans, and supervise actions across multiple subordinate agents; however, as a subagent, it focuses on its specified responsibilities, understands the tools at its disposal, and knows when to escalate concerns. Furthermore, the model boasts the capacity to handle a context window of 1 million tokens, which empowers it to remember previous actions, retrieve information from much earlier tasks, and condense context for enhanced efficiency. As a result of these features, the Meta Model API signifies a major leap forward in the creation of intelligent and responsive software applications, paving the way for future innovations in technology. This advancement not only benefits developers but also enhances the user experience by enabling more sophisticated interactions with digital tools.

PinAppAI serves as a visual feedback platform that effectively converts requests for changes to websites into well-structured tasks suitable for AI coding agents. Users can easily place pins on different elements of an active website and express their desired modifications through straightforward text or voice commands. The AI agents, including Claude Code and Codex, receive these comprehensive requests, which detail specific elements, text selections, and precise visual captures. The platform features four unique pinning modes: free-form pins that utilize percentage-based positioning, element pins for accurate targeting of HTML elements, screenshot pins for precise image captures, and text-selection pins that make find-and-replace tasks straightforward. PinAppAI integrates smoothly with AI coding solutions via the Model Context Protocol, allowing reviewers to make annotations directly on live sites while AI agents propose modifications within the editing environment. It supports multiple AI tools, such as Claude Code, Cursor, Continue, Codex, and Claude Desktop. Users can engage with PinAppAI through various methods, including review links, embedded widgets, a Chrome extension, and a macOS application, providing flexibility and ease of use for a diverse range of users. This all-encompassing approach not only streamlines web development processes but also enhances collaboration among team members, making it an invaluable resource in the digital landscape.

Together AI powers the next generation of AI-native software with a cloud platform designed around high-efficiency training, fine-tuning, and large-scale inference. Built on research-driven optimizations, the platform enables customers to run massive workloads—often reaching trillions of tokens—without bottlenecks or degraded performance. Its GPU clusters are engineered for peak throughput, offering self-service NVIDIA infrastructure, instant provisioning, and optimized distributed training configurations. Together AI’s model library spans open-source giants, specialized reasoning models, multimodal systems for images and videos, and high-performance LLMs like Qwen3, DeepSeek-V3.1, and GPT-OSS. Developers migrating from closed-model ecosystems benefit from API compatibility and flexible inference solutions. Innovations such as the ATLAS runtime-learning accelerator, FlashAttention, RedPajama datasets, Dragonfly, and Open Deep Research demonstrate the company’s leadership in AI systems research. The platform's fine-tuning suite supports larger models and longer contexts, while the Batch Inference API enables billions of tokens to be processed at up to 50% lower cost. Customer success stories highlight breakthroughs in inference speed, video generation economics, and large-scale training efficiency. Combined with predictable performance and high availability, Together AI enables teams to deploy advanced AI pipelines rapidly and reliably. For organizations racing toward large-scale AI innovation, Together AI provides the infrastructure, research, and tooling needed to operate at frontier-level performance.

Models can be accessed either via the integrated Chat UI of the application or by setting up a local server compatible with OpenAI. The essential requirements for this setup include an M1, M2, or M3 Mac, or a Windows PC with a processor that has AVX2 instruction support. Currently, Linux support is available in its beta phase. A significant benefit of using a local LLM is the strong focus on privacy, which is a fundamental aspect of LM Studio, ensuring that your data remains secure and exclusively on your personal device. Moreover, you can run LLMs that you import into LM Studio using an API server hosted on your own machine. This arrangement not only enhances security but also provides a customized experience when interacting with language models. Ultimately, such a configuration allows for greater control and peace of mind regarding your information while utilizing advanced language processing capabilities.

Requesty is a cutting-edge platform designed to optimize AI workloads by intelligently routing requests to the most appropriate model for each individual task. It features advanced functionalities such as automatic fallback systems and efficient queuing mechanisms, ensuring uninterrupted service availability even when some models may be out of service temporarily. With support for a wide range of models, including GPT-4, Claude 3.5, and DeepSeek, Requesty also offers observability for AI applications, allowing users to track model performance and adjust their application usage for maximum effectiveness. By reducing API costs and enhancing operational efficiency, Requesty empowers developers with the necessary tools to build more intelligent and reliable AI solutions. This platform not only fine-tunes performance but also encourages innovation within the AI landscape, creating opportunities for the development of transformative applications. As a result, developers can push the boundaries of what AI can achieve, leading to more sophisticated and impactful technologies.

GHOSTMETAL provides a sophisticated, web-based AI chat platform along with an API tailored for applications that incorporate both language and image processing models. Among its offerings is the GLM-5.3 model, which boasts a context window of 256K, the GLM-5.3-long model featuring a 1M context window, and the Qwen-3.8 model, which is equipped with web search integration as well as tools for creating and editing images. Furthermore, the OpenAI-compatible REST API facilitates real-time data streaming and is compatible with a variety of clients such as Cursor, Cline, Continue, SillyTavern, Agnai, LangChain, and OpenAI SDKs. This platform serves a diverse audience, including individual users and developers who harness AI technologies for a range of tasks, from software development to writing and creative endeavors. Users can choose to pay using prepaid credits or opt for monthly subscription plans while maintaining the ability to manage separate API tokens tailored for different applications. GHOSTMETAL operates its services on proprietary hardware, ensuring that prompts and responses are processed in memory, which safeguards chat histories and images within the user's browser environment. This thoughtful architecture prioritizes user privacy and data integrity, positioning GHOSTMETAL as an appealing option for those seeking reliable and secure AI solutions, ultimately facilitating a seamless user experience across various applications.

Claude for Legal is a sophisticated AI assistant crafted by Anthropic, tailored for the needs of legal professionals to enhance their document management and research capabilities. This innovative tool excels at summarizing lengthy documents, extracting and comparing essential information, drafting and editing text, and assisting with the analysis of contracts and various legal papers. Legal teams across law firms and corporations can utilize Claude for Legal to optimize their document workflows and access vital knowledge, ensuring they have important context and source materials readily available. Furthermore, users are encouraged to evaluate the AI-generated outputs as an integral part of their overall workflow, which adds a layer of scrutiny to the process. Accessible on both desktop and mobile devices, Claude for Legal not only simplifies information processing and content creation but also emphasizes the importance of user verification. It's crucial for users to exercise their professional judgment and make well-informed legal decisions independently within their practice. Thus, while the AI can significantly boost efficiency, the ultimate accountability for legal accuracy and compliance continues to rest with the individual practitioner. In this way, Claude for Legal acts as a powerful ally, enhancing productivity while still necessitating human oversight in legal matters.