Alternatives to Microsoft Foundry Models

Compare Microsoft Foundry Models alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Microsoft Foundry Models in 2025. Compare features, ratings, user reviews, pricing, and more from Microsoft Foundry Models competitors and alternatives in order to make an informed decision for your business.

  • 1
    Vertex AI
    Build, deploy, and scale machine learning (ML) models faster, with fully managed ML tools for any use case. Through Vertex AI Workbench, Vertex AI is natively integrated with BigQuery, Dataproc, and Spark. You can use BigQuery ML to create and execute machine learning models in BigQuery using standard SQL queries on existing business intelligence tools and spreadsheets, or you can export datasets from BigQuery directly into Vertex AI Workbench and run your models from there. Use Vertex Data Labeling to generate highly accurate labels for your data collection. Vertex AI Agent Builder enables developers to create and deploy enterprise-grade generative AI applications. It offers both no-code and code-first approaches, allowing users to build AI agents using natural language instructions or by leveraging frameworks like LangChain and LlamaIndex.
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  • 2
    Mistral AI

    Mistral AI

    Mistral AI

    Mistral AI is a pioneering artificial intelligence startup specializing in open-source generative AI. The company offers a range of customizable, enterprise-grade AI solutions deployable across various platforms, including on-premises, cloud, edge, and devices. Flagship products include "Le Chat," a multilingual AI assistant designed to enhance productivity in both personal and professional contexts, and "La Plateforme," a developer platform that enables the creation and deployment of AI-powered applications. Committed to transparency and innovation, Mistral AI positions itself as a leading independent AI lab, contributing significantly to open-source AI and policy development.
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    Amazon Bedrock
    Amazon Bedrock is a fully managed service that simplifies building and scaling generative AI applications by providing access to a variety of high-performing foundation models (FMs) from leading AI companies such as AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon itself. Through a single API, developers can experiment with these models, customize them using techniques like fine-tuning and Retrieval Augmented Generation (RAG), and create agents that interact with enterprise systems and data sources. As a serverless platform, Amazon Bedrock eliminates the need for infrastructure management, allowing seamless integration of generative AI capabilities into applications with a focus on security, privacy, and responsible AI practices.
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    Microsoft Foundry
    Microsoft Foundry is an end-to-end platform for building, optimizing, and governing AI apps and agents at scale. It gives developers access to more than 11,000 models — from foundational to multimodal — all available through one unified interface. With a simple, interoperable API and SDK, teams can build faster, ship confidently, and reduce integration complexity. Foundry connects seamlessly with your business systems, enabling AI solutions that understand your data and operate securely across your organization. Built-in governance, monitoring, and fleetwide controls ensure responsible AI deployment from day one. Microsoft Foundry helps companies turn AI into real business impact with speed, security, and precision.
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    Phi-4-reasoning-plus
    Phi-4-reasoning-plus is a 14-billion parameter open-weight reasoning model that builds upon Phi-4-reasoning capabilities. It is further trained with reinforcement learning to utilize more inference-time compute, using 1.5x more tokens than Phi-4-reasoning, to deliver higher accuracy. Despite its significantly smaller size, Phi-4-reasoning-plus achieves better performance than OpenAI o1-mini and DeepSeek-R1 at most benchmarks, including mathematical reasoning and Ph.D. level science questions. It surpasses the full DeepSeek-R1 model (with 671 billion parameters) on the AIME 2025 test, the 2025 qualifier for the USA Math Olympiad. Phi-4-reasoning-plus is available on Azure AI Foundry and HuggingFace.
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    Foundry Local

    Foundry Local

    Microsoft

    Foundry Local is a local version of Azure AI Foundry that enables local execution of large language models (LLMs) directly on your Windows device. This on-device AI inference solution provides privacy, customization, and cost benefits compared to cloud-based alternatives. Best of all, it fits into your existing workflows and applications with an easy-to-use CLI and REST API.
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    Microsoft Foundry Agent Service
    Microsoft Foundry Agent Service is a secure, enterprise-ready platform for designing, deploying, and orchestrating AI agents at scale. It gives teams a streamlined interface and toolset to automate complex workflows using multi-agent systems. Developers can build with hosted agents, custom code, or agent frameworks while taking advantage of Azure’s reliability, scalability, and integrated observability. Built-in tools, enterprise connectors, and Model Context Protocol support make it easy for agents to interact with business systems and organizational data. Security, access governance, and compliance are embedded throughout, allowing companies to maintain full control while deploying intelligent automation across critical processes. With one-click deployment to Microsoft 365 experiences, Foundry Agent Service accelerates how organizations operationalize AI in everyday work.
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    Phi-4

    Phi-4

    Microsoft

    Phi-4 is a 14B parameter state-of-the-art small language model (SLM) that excels at complex reasoning in areas such as math, in addition to conventional language processing. Phi-4 is the latest member of our Phi family of small language models and demonstrates what’s possible as we continue to probe the boundaries of SLMs. Phi-4 is currently available on Azure AI Foundry under a Microsoft Research License Agreement (MSRLA) and will be available on Hugging Face. Phi-4 outperforms comparable and larger models on math related reasoning due to advancements throughout the processes, including the use of high-quality synthetic datasets, curation of high-quality organic data, and post-training innovations. Phi-4 continues to push the frontier of size vs quality.
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    Oumi

    Oumi

    Oumi

    Oumi is a fully open source platform that streamlines the entire lifecycle of foundation models, from data preparation and training to evaluation and deployment. It supports training and fine-tuning models ranging from 10 million to 405 billion parameters using state-of-the-art techniques such as SFT, LoRA, QLoRA, and DPO. The platform accommodates both text and multimodal models, including architectures like Llama, DeepSeek, Qwen, and Phi. Oumi offers tools for data synthesis and curation, enabling users to generate and manage training datasets effectively. For deployment, it integrates with popular inference engines like vLLM and SGLang, ensuring efficient model serving. The platform also provides comprehensive evaluation capabilities across standard benchmarks to assess model performance. Designed for flexibility, Oumi can run on various environments, from local laptops to cloud infrastructures such as AWS, Azure, GCP, and Lambda.
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    OpenPipe

    OpenPipe

    OpenPipe

    OpenPipe provides fine-tuning for developers. Keep your datasets, models, and evaluations all in one place. Train new models with the click of a button. Automatically record LLM requests and responses. Create datasets from your captured data. Train multiple base models on the same dataset. We serve your model on our managed endpoints that scale to millions of requests. Write evaluations and compare model outputs side by side. Change a couple of lines of code, and you're good to go. Simply replace your Python or Javascript OpenAI SDK and add an OpenPipe API key. Make your data searchable with custom tags. Small specialized models cost much less to run than large multipurpose LLMs. Replace prompts with models in minutes, not weeks. Fine-tuned Mistral and Llama 2 models consistently outperform GPT-4-1106-Turbo, at a fraction of the cost. We're open-source, and so are many of the base models we use. Own your own weights when you fine-tune Mistral and Llama 2, and download them at any time.
    Starting Price: $1.20 per 1M tokens
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    Azure OpenAI Service
    Apply advanced coding and language models to a variety of use cases. Leverage large-scale, generative AI models with deep understandings of language and code to enable new reasoning and comprehension capabilities for building cutting-edge applications. Apply these coding and language models to a variety of use cases, such as writing assistance, code generation, and reasoning over data. Detect and mitigate harmful use with built-in responsible AI and access enterprise-grade Azure security. Gain access to generative models that have been pretrained with trillions of words. Apply them to new scenarios including language, code, reasoning, inferencing, and comprehension. Customize generative models with labeled data for your specific scenario using a simple REST API. Fine-tune your model's hyperparameters to increase accuracy of outputs. Use the few-shot learning capability to provide the API with examples and achieve more relevant results.
    Starting Price: $0.0004 per 1000 tokens
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    Phi-4-mini-flash-reasoning
    Phi-4-mini-flash-reasoning is a 3.8 billion‑parameter open model in Microsoft’s Phi family, purpose‑built for edge, mobile, and other resource‑constrained environments where compute, memory, and latency are tightly limited. It introduces the SambaY decoder‑hybrid‑decoder architecture with Gated Memory Units (GMUs) interleaved alongside Mamba state‑space and sliding‑window attention layers, delivering up to 10× higher throughput and a 2–3× reduction in latency compared to its predecessor without sacrificing advanced math and logic reasoning performance. Supporting a 64 K‑token context length and fine‑tuned on high‑quality synthetic data, it excels at long‑context retrieval, reasoning tasks, and real‑time inference, all deployable on a single GPU. Phi-4-mini-flash-reasoning is available today via Azure AI Foundry, NVIDIA API Catalog, and Hugging Face, enabling developers to build fast, scalable, logic‑intensive applications.
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    Mistral Large

    Mistral Large

    Mistral AI

    Mistral Large is Mistral AI's flagship language model, designed for advanced text generation and complex multilingual reasoning tasks, including text comprehension, transformation, and code generation. It supports English, French, Spanish, German, and Italian, offering a nuanced understanding of grammar and cultural contexts. With a 32,000-token context window, it can accurately recall information from extensive documents. The model's precise instruction-following and native function-calling capabilities facilitate application development and tech stack modernization. Mistral Large is accessible through Mistral's platform, Azure AI Studio, and Azure Machine Learning, and can be self-deployed for sensitive use cases. Benchmark evaluations indicate that Mistral Large achieves strong results, making it the world's second-ranked model generally available through an API, next to GPT-4.
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    DeepSeek R1

    DeepSeek R1

    DeepSeek

    DeepSeek-R1 is an advanced open-source reasoning model developed by DeepSeek, designed to rival OpenAI's Model o1. Accessible via web, app, and API, it excels in complex tasks such as mathematics and coding, demonstrating superior performance on benchmarks like the American Invitational Mathematics Examination (AIME) and MATH. DeepSeek-R1 employs a mixture of experts (MoE) architecture with 671 billion total parameters, activating 37 billion parameters per token, enabling efficient and accurate reasoning capabilities. This model is part of DeepSeek's commitment to advancing artificial general intelligence (AGI) through open-source innovation.
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    Command A Translate
    Command A Translate is Cohere’s enterprise-grade machine translation model crafted to deliver secure, high-quality translation across 23 business-relevant languages. Built on a powerful 111-billion-parameter architecture with an 8K-input / 8K-output context window, it achieves industry-leading performance that surpasses models like GPT-5, DeepSeek-V3, DeepL Pro, and Google Translate across a broad suite of benchmarks. The model supports private deployments for sensitive workflows, allowing enterprises full control over their data, and introduces an innovative “Deep Translation” workflow, an agentic, multi-step refinement process that iteratively enhances translation quality for complex use cases. External validation from RWS Group confirms its excellence in challenging translation tasks. Additionally, the model’s weights are available for research via Hugging Face under a CC-BY-NC license, enabling deep customization, fine-tuning, and private deployment flexibility.
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    Klu

    Klu

    Klu

    Klu.ai is a Generative AI platform that simplifies the process of designing, deploying, and optimizing AI applications. Klu integrates with your preferred Large Language Models, incorporating data from varied sources, giving your applications unique context. Klu accelerates building applications using language models like Anthropic Claude, Azure OpenAI, GPT-4, and over 15 other models, allowing rapid prompt/model experimentation, data gathering and user feedback, and model fine-tuning while cost-effectively optimizing performance. Ship prompt generations, chat experiences, workflows, and autonomous workers in minutes. Klu provides SDKs and an API-first approach for all capabilities to enable developer productivity. Klu automatically provides abstractions for common LLM/GenAI use cases, including: LLM connectors, vector storage and retrieval, prompt templates, observability, and evaluation/testing tooling.
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    Phi-2

    Phi-2

    Microsoft

    We are now releasing Phi-2, a 2.7 billion-parameter language model that demonstrates outstanding reasoning and language understanding capabilities, showcasing state-of-the-art performance among base language models with less than 13 billion parameters. On complex benchmarks Phi-2 matches or outperforms models up to 25x larger, thanks to new innovations in model scaling and training data curation. With its compact size, Phi-2 is an ideal playground for researchers, including for exploration around mechanistic interpretability, safety improvements, or fine-tuning experimentation on a variety of tasks. We have made Phi-2 available in the Azure AI Studio model catalog to foster research and development on language models.
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    DeepSeek V3.1
    DeepSeek V3.1 is a groundbreaking open-weight large language model featuring a massive 685-billion parameters and an extended 128,000‑token context window, enabling it to process documents equivalent to 400-page books in a single prompt. It delivers integrated capabilities for chat, reasoning, and code generation within a unified hybrid architecture, seamlessly blending these functions into one coherent model. V3.1 supports a variety of tensor formats to give developers flexibility in optimizing performance across different hardware. Early benchmark results show robust performance, including a 71.6% score on the Aider coding benchmark, putting it on par with or ahead of systems like Claude Opus 4 and doing so at a far lower cost. Made available under an open source license on Hugging Face with minimal fanfare, DeepSeek V3.1 is poised to reshape access to high-performance AI, challenging traditional proprietary models.
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    Devs.ai

    Devs.ai

    Devs.ai

    Devs.ai is a platform that enables users to create unlimited AI agents in minutes without requiring credit card information. It provides access to major AI models from providers such as Meta, Anthropic, OpenAI, Gemini, and Cohere, allowing users to select the most suitable large language model for their specific business purposes. Devs.ai features a low/no-code solution, empowering users to effortlessly create tailor-made AI agents for their business and clientele. Emphasizing enterprise-grade governance, Devs.ai ensures that organizations can build AI using even the most sensitive data, maintaining meticulous oversight and control over AI implementations. The collaborative workspace fosters seamless teamwork, enabling teams to gain new insights, unlock innovation, and increase productivity. Users can train their AI with proprietary assets to derive results pertinent to their business, unlocking unique insights.
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    CodeNext

    CodeNext

    CodeNext

    CodeNext.ai is an AI-powered coding assistant designed specifically for Xcode developers, offering context-aware code completion and agentic chat functionalities. It supports a wide range of leading AI models, including OpenAI, Azure OpenAI, Google AI, Mistral, Anthropic, Deepseek, Ollama, and more, providing developers with the flexibility to choose and switch between models as needed. It delivers intelligent, real-time code suggestions as you type, enhancing productivity and coding efficiency. Its agentic chat feature allows developers to interact in natural language to write code, fix bugs, refactor, and perform various coding tasks within or beyond the codebase. CodeNext.ai includes custom chat plugins that enable the execution of terminal commands and shortcuts directly within the chat interface, streamlining the development workflow.
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    Tune AI

    Tune AI

    NimbleBox

    Leverage the power of custom models to build your competitive advantage. With our enterprise Gen AI stack, go beyond your imagination and offload manual tasks to powerful assistants instantly – the sky is the limit. For enterprises where data security is paramount, fine-tune and deploy generative AI models on your own cloud, securely.
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    DeepSeek R2

    DeepSeek R2

    DeepSeek

    DeepSeek R2 is the anticipated successor to DeepSeek R1, a groundbreaking AI reasoning model launched in January 2025 by the Chinese AI startup DeepSeek. Building on R1’s success, which disrupted the AI industry with its cost-effective performance rivaling top-tier models like OpenAI’s o1, R2 promises a quantum leap in capabilities. It is expected to deliver exceptional speed and human-like reasoning, excelling in complex tasks such as advanced coding and high-level mathematical problem-solving. Leveraging DeepSeek’s innovative Mixture-of-Experts architecture and efficient training methods, R2 aims to outperform its predecessor while maintaining a low computational footprint, potentially expanding its reasoning abilities to languages beyond English.
  • 23
    bolt.diy

    bolt.diy

    bolt.diy

    bolt.diy is an open-source platform that enables developers to easily create, run, edit, and deploy full-stack web applications with a variety of large language models (LLMs). It supports a wide range of models, including OpenAI, Anthropic, Ollama, OpenRouter, Gemini, LMStudio, Mistral, xAI, HuggingFace, DeepSeek, and Groq. The platform offers seamless integration through the Vercel AI SDK, allowing users to customize and extend their applications with the LLMs of their choice. With its intuitive interface, bolt.diy is designed to simplify AI development workflows, making it a great tool for both experimentation and production-ready applications.
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    Falcon Mamba 7B

    Falcon Mamba 7B

    Technology Innovation Institute (TII)

    Falcon Mamba 7B is the first open-source State Space Language Model (SSLM), introducing a groundbreaking architecture for Falcon models. Recognized as the top-performing open-source SSLM worldwide by Hugging Face, it sets a new benchmark in AI efficiency. Unlike traditional transformers, SSLMs operate with minimal memory requirements and can generate extended text sequences without additional overhead. Falcon Mamba 7B surpasses leading transformer-based models, including Meta’s Llama 3.1 8B and Mistral’s 7B, showcasing superior performance. This innovation underscores Abu Dhabi’s commitment to advancing AI research and development on a global scale.
  • 25
    Mistral 7B

    Mistral 7B

    Mistral AI

    Mistral 7B is a 7.3-billion-parameter language model that outperforms larger models like Llama 2 13B across various benchmarks. It employs Grouped-Query Attention (GQA) for faster inference and Sliding Window Attention (SWA) to efficiently handle longer sequences. Released under the Apache 2.0 license, Mistral 7B is accessible for deployment across diverse platforms, including local environments and major cloud services. Additionally, a fine-tuned version, Mistral 7B Instruct, demonstrates enhanced performance in instruction-following tasks, surpassing models like Llama 2 13B Chat.
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    Mistral Large 3
    Mistral Large 3 is a next-generation, open multimodal AI model built with a powerful sparse Mixture-of-Experts architecture featuring 41B active parameters out of 675B total. Designed from scratch on NVIDIA H200 GPUs, it delivers frontier-level reasoning, multilingual performance, and advanced image understanding while remaining fully open-weight under the Apache 2.0 license. The model achieves top-tier results on modern instruction benchmarks, positioning it among the strongest permissively licensed foundation models available today. With native support across vLLM, TensorRT-LLM, and major cloud providers, Mistral Large 3 offers exceptional accessibility and performance efficiency. Its design enables enterprise-grade customization, letting teams fine-tune or adapt the model for domain-specific workflows and proprietary applications. Mistral Large 3 represents a major advancement in open AI, offering frontier intelligence without sacrificing transparency or control.
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    Command A Reasoning
    Command A Reasoning is Cohere’s most advanced enterprise-ready language model, engineered for high-stakes reasoning tasks and seamless integration into AI agent workflows. The model delivers exceptional reasoning performance, efficiency, and controllability, scaling across multi-GPU setups with support for up to 256,000-token context windows, ideal for handling long documents and multi-step agentic tasks. Organizations can fine-tune output precision and latency through a token budget, allowing a single model to flexibly serve both high-accuracy and high-throughput use cases. It powers Cohere’s North platform with leading benchmark performance and excels in multilingual contexts across 23 languages. Designed with enterprise safety in mind, it balances helpfulness with robust safeguards against harmful outputs. A lightweight deployment option allows running the model securely on a single H100 or A100 GPU, simplifying private, scalable use.
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    OpenAI o3
    OpenAI o3 is an advanced AI model designed to enhance reasoning capabilities by breaking down complex instructions into smaller, more manageable steps. It offers significant improvements over previous AI iterations, excelling in coding tasks, competitive programming, and achieving high scores in mathematics and science benchmarks. Available for widespread use, OpenAI o3 supports advanced AI-driven problem-solving and decision-making processes. The model incorporates deliberative alignment techniques to ensure its responses align with established safety and ethical guidelines, making it a powerful tool for developers, researchers, and enterprises seeking sophisticated AI solutions.
    Starting Price: $2 per 1 million tokens
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    Mistral Medium 3.1
    Mistral Medium 3.1 is the latest frontier-class multimodal foundation model released in August 2025, designed to deliver advanced reasoning, coding, and multimodal capabilities while dramatically reducing deployment complexity and costs. It builds on the highly efficient architecture of Mistral Medium 3, renowned for offering state-of-the-art performance at up to 8-times lower cost than leading large models, enhancing tone consistency, responsiveness, and accuracy across diverse tasks and modalities. The model supports deployment across hybrid environments, on-premises systems, and virtual private clouds, and it achieves competitive performance relative to high-end models such as Claude Sonnet 3.7, Llama 4 Maverick, and Cohere Command A. Ideal for professional and enterprise use cases, Mistral Medium 3.1 excels in coding, STEM reasoning, language understanding, and multimodal comprehension, while maintaining broad compatibility with custom workflows and infrastructure.
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    Mistral Small

    Mistral Small

    Mistral AI

    On September 17, 2024, Mistral AI announced several key updates to enhance the accessibility and performance of their AI offerings. They introduced a free tier on "La Plateforme," their serverless platform for tuning and deploying Mistral models as API endpoints, enabling developers to experiment and prototype at no cost. Additionally, Mistral AI reduced prices across their entire model lineup, with significant cuts such as a 50% reduction for Mistral Nemo and an 80% decrease for Mistral Small and Codestral, making advanced AI more cost-effective for users. The company also unveiled Mistral Small v24.09, a 22-billion-parameter model offering a balance between performance and efficiency, suitable for tasks like translation, summarization, and sentiment analysis. Furthermore, they made Pixtral 12B, a vision-capable model with image understanding capabilities, freely available on "Le Chat," allowing users to analyze and caption images without compromising text-based performance.
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    PygmalionAI

    PygmalionAI

    PygmalionAI

    PygmalionAI is a community dedicated to creating open-source projects based on EleutherAI's GPT-J 6B and Meta's LLaMA models. In simple terms, Pygmalion makes AI fine-tuned for chatting and roleplaying purposes. The current actively supported Pygmalion AI model is the 7B variant, based on Meta AI's LLaMA model. With only 18GB (or less) VRAM required, Pygmalion offers better chat capability than much larger language models with relatively minimal resources. Our curated dataset of high-quality roleplaying data ensures that your bot will be the optimal RP partner. Both the model weights and the code used to train it are completely open-source, and you can modify/re-distribute it for whatever purpose you want. Language models, including Pygmalion, generally run on GPUs since they need access to fast memory and massive processing power in order to output coherent text at an acceptable speed.
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    Azure Open Datasets
    Improve the accuracy of your machine learning models with publicly available datasets. Save time on data discovery and preparation by using curated datasets that are ready to use in machine learning workflows and easy to access from Azure services. Account for real-world factors that can impact business outcomes. By incorporating features from curated datasets into your machine learning models, improve the accuracy of predictions and reduce data preparation time. Share datasets with a growing community of data scientists and developers. Deliver insights at hyperscale using Azure Open Datasets with Azure’s machine learning and data analytics solutions. There's no additional charge for using most Open Datasets. Pay only for Azure services consumed while using Open Datasets, such as virtual machine instances, storage, networking resources, and machine learning. Curated open data made easily accessible on Azure.
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    Mistral AI Studio
    Mistral AI Studio is a unified builder-platform that enables organizations and development teams to design, customize, deploy, and manage advanced AI agents, models, and workflows from proof-of-concept through to production. The platform offers reusable blocks, including agents, tools, connectors, guardrails, datasets, workflows, and evaluations, combined with observability and telemetry capabilities so you can track agent performance, trace root causes, and govern production AI operations with visibility. With modules like Agent Runtime to make multi-step AI behaviors repeatable and shareable, AI Registry to catalogue and manage model assets, and Data & Tool Connections for seamless integration with enterprise systems, Studio supports everything from fine-tuning open source models to embedding them in your infrastructure and rolling out enterprise-grade AI solutions.
    Starting Price: $14.99 per month
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    Mistral Small 3.1
    ​Mistral Small 3.1 is a state-of-the-art, multimodal, and multilingual AI model released under the Apache 2.0 license. Building upon Mistral Small 3, this enhanced version offers improved text performance, and advanced multimodal understanding, and supports an expanded context window of up to 128,000 tokens. It outperforms comparable models like Gemma 3 and GPT-4o Mini, delivering inference speeds of 150 tokens per second. Designed for versatility, Mistral Small 3.1 excels in tasks such as instruction following, conversational assistance, image understanding, and function calling, making it suitable for both enterprise and consumer-grade AI applications. Its lightweight architecture allows it to run efficiently on a single RTX 4090 or a Mac with 32GB RAM, facilitating on-device deployments. It is available for download on Hugging Face, accessible via Mistral AI's developer playground, and integrated into platforms like Google Cloud Vertex AI, with availability on NVIDIA NIM and
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    Neum AI

    Neum AI

    Neum AI

    No one wants their AI to respond with out-of-date information to a customer. ‍Neum AI helps companies have accurate and up-to-date context in their AI applications. Use built-in connectors for data sources like Amazon S3 and Azure Blob Storage, vector stores like Pinecone and Weaviate to set up your data pipelines in minutes. Supercharge your data pipeline by transforming and embedding your data with built-in connectors for embedding models like OpenAI and Replicate, and serverless functions like Azure Functions and AWS Lambda. Leverage role-based access controls to make sure only the right people can access specific vectors. Bring your own embedding models, vector stores and sources. Ask us about how you can even run Neum AI in your own cloud.
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    Qwen2.5-Max
    Qwen2.5-Max is a large-scale Mixture-of-Experts (MoE) model developed by the Qwen team, pretrained on over 20 trillion tokens and further refined through Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF). In evaluations, it outperforms models like DeepSeek V3 in benchmarks such as Arena-Hard, LiveBench, LiveCodeBench, and GPQA-Diamond, while also demonstrating competitive results in other assessments, including MMLU-Pro. Qwen2.5-Max is accessible via API through Alibaba Cloud and can be explored interactively on Qwen Chat.
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    Supernovas AI LLM

    Supernovas AI LLM

    Supernovas AI LLM

    Supernovas AI is a unified, team‑focused AI workspace that provides seamless access to all leading LLMs—including GPT‑4.1/4.5 Turbo, Claude Haiku/Sonnet/Opus, Gemini 2.5 Pro/Pro, Azure OpenAI, AWS Bedrock, Mistral, Meta LLaMA, Deepseek, Qwen, and more—through a single, secure interface. It offers essential chat tools like model access, prompt templates, bookmarks, static artifacts, and integrated web search, along with advanced features such as Model Context Protocol (MCP), a talk-to-your data knowledge base, built-in image generation and editing, memory‑enabled agents, and code execution. Supernovas AI simplifies AI tool management by eliminating multiple subscriptions and API keys, enabling fast onboarding and enterprise-grade privacy and collaboration—all from one streamlined platform.
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    Martian

    Martian

    Martian

    By using the best-performing model for each request, we can achieve higher performance than any single model. Martian outperforms GPT-4 across OpenAI's evals (open/evals). We turn opaque black boxes into interpretable representations. Our router is the first tool built on top of our model mapping method. We are developing many other applications of model mapping including turning transformers from indecipherable matrices into human-readable programs. If a company experiences an outage or high latency period, automatically reroute to other providers so your customers never experience any issues. Determine how much you could save by using the Martian Model Router with our interactive cost calculator. Input your number of users, tokens per session, and sessions per month, and specify your cost/quality tradeoff.
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    DeepSeek-V3.2-Exp
    Introducing DeepSeek-V3.2-Exp, our latest experimental model built on V3.1-Terminus, debuting DeepSeek Sparse Attention (DSA) for faster and more efficient inference and training on long contexts. DSA enables fine-grained sparse attention with minimal loss in output quality, boosting performance for long-context tasks while reducing compute costs. Benchmarks indicate that V3.2-Exp performs on par with V3.1-Terminus despite these efficiency gains. The model is now live across app, web, and API. Alongside this, the DeepSeek API prices have been cut by over 50% immediately to make access more affordable. For a transitional period, users can still access V3.1-Terminus via a temporary API endpoint until October 15, 2025. DeepSeek welcomes feedback on DSA via its feedback portal. In conjunction with the release, DeepSeek-V3.2-Exp has been open-sourced: the model weights and supporting technology (including key GPU kernels in TileLang and CUDA) are available on Hugging Face.
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    Open R1

    Open R1

    Open R1

    Open R1 is a community-driven, open-source initiative aimed at replicating the advanced AI capabilities of DeepSeek-R1 through transparent methodologies. You can try Open R1 AI model or DeepSeek R1 free online chat on Open R1. The project offers a comprehensive implementation of DeepSeek-R1's reasoning-optimized training pipeline, including tools for GRPO training, SFT fine-tuning, and synthetic data generation, all under the MIT license. While the original training data remains proprietary, Open R1 provides the complete toolchain for users to develop and fine-tune their own models.
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    Simplismart

    Simplismart

    Simplismart

    Fine-tune and deploy AI models with Simplismart's fastest inference engine. Integrate with AWS/Azure/GCP and many more cloud providers for simple, scalable, cost-effective deployment. Import open source models from popular online repositories or deploy your own custom model. Leverage your own cloud resources or let Simplismart host your model. With Simplismart, you can go far beyond AI model deployment. You can train, deploy, and observe any ML model and realize increased inference speeds at lower costs. Import any dataset and fine-tune open-source or custom models rapidly. Run multiple training experiments in parallel efficiently to speed up your workflow. Deploy any model on our endpoints or your own VPC/premise and see greater performance at lower costs. Streamlined and intuitive deployment is now a reality. Monitor GPU utilization and all your node clusters in one dashboard. Detect any resource constraints and model inefficiencies on the go.
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    GradientJ

    GradientJ

    GradientJ

    GradientJ provides everything you need to build large language model applications in minutes and manage them forever. Discover and maintain the best prompts by saving versions and comparing them across benchmark examples. Orchestrate and manage complex applications by chaining prompts and knowledge bases into complex APIs. Enhance the accuracy of your models by integrating them with your proprietary data.
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    Magistral

    Magistral

    Mistral AI

    Magistral is Mistral AI’s first reasoning‑focused language model family, released in two sizes: Magistral Small, a 24 B‑parameter open‑weight model under Apache 2.0 (downloadable on Hugging Face), and Magistral Medium, a more capable enterprise version available via Mistral’s API, Le Chat platform, and major cloud marketplaces. Built for domain‑specific, transparent, multilingual reasoning across tasks like math, physics, structured calculations, programmatic logic, decision trees, and rule‑based systems, Magistral produces chain‑of‑thought outputs in the user’s language that you can follow and verify. This launch marks a shift toward compact yet powerful transparent AI reasoning. Magistral Medium is currently available in preview on Le Chat, the API, SageMaker, WatsonX, Azure AI, and Google Cloud Marketplace. Magistral is ideal for general-purpose use requiring longer thought processing and better accuracy than with non-reasoning LLMs.
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    Palantir Foundry

    Palantir Foundry

    Palantir Technologies

    Foundry is a transformative data platform built to help solve the modern enterprise’s most critical problems by creating a central operating system for an organization’s data, while securely integrating siloed data sources into a common analytics and operations picture. Palantir works with commercial companies and government organizations alike to close the operational loop, feeding real-time data into your data science models and updating source systems. With a breadth of industry-leading capabilities, Palantir can help enterprises traverse and operationalize data to enable and scale decision-making, alongside best-in-class security, data protection, and governance. Foundry was named by Forrester as a leader in the The Forrester Wave™: AI/ML Platforms, Q3 2022. Scoring the highest marks possible in product vision, performance, market approach, and applications criteria. As a Dresner-Award winning platform, Foundry is the overall leader in the BI and Analytics market and rate
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    Mirascope

    Mirascope

    Mirascope

    Mirascope is an open-source library built on Pydantic 2.0 for the most clean, and extensible prompt management and LLM application building experience. Mirascope is a powerful, flexible, and user-friendly library that simplifies the process of working with LLMs through a unified interface that works across various supported providers, including OpenAI, Anthropic, Mistral, Gemini, Groq, Cohere, LiteLLM, Azure AI, Vertex AI, and Bedrock. Whether you're generating text, extracting structured information, or developing complex AI-driven agent systems, Mirascope provides the tools you need to streamline your development process and create powerful, robust applications. Response models in Mirascope allow you to structure and validate the output from LLMs. This feature is particularly useful when you need to ensure that the LLM's response adheres to a specific format or contains certain fields.
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    IBM Cloud Foundry
    Cloud Foundry ensures that the build and deploy aspects of coding remain carefully coordinated with any attached services — resulting in quick, consistent and reliable iterating of applications. As an industry-standard platform as a service (PaaS), Cloud Foundry ensures the fastest, easiest and most reliable deployment of cloud-native applications. IBM offers the Cloud Foundry PaaS in several hosting models, allowing you to customize your PaaS experience and balance a range of considerations, including price, deployment speed and security. Cloud Foundry includes runtimes for Java, Node.js, PHP, Python, Ruby, ASP.NET, Tomcat, Swift and Go. Community build packs are also available. Combined with DevOps services, the application runtimes enable a delivery pipeline that automates much of the iterative development process.
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    DeepScaleR

    DeepScaleR

    Agentica Project

    DeepScaleR is a 1.5-billion-parameter language model fine-tuned from DeepSeek-R1-Distilled-Qwen-1.5B using distributed reinforcement learning and a novel iterative context-lengthening strategy that gradually increases its context window from 8K to 24K tokens during training. It was trained on ~40,000 carefully curated mathematical problems drawn from competition-level datasets like AIME (1984–2023), AMC (pre-2023), Omni-MATH, and STILL. DeepScaleR achieves 43.1% accuracy on AIME 2024, a roughly 14.3 percentage point boost over the base model, and surpasses the performance of the proprietary O1-Preview model despite its much smaller size. It also posts strong results on a suite of math benchmarks (e.g., MATH-500, AMC 2023, Minerva Math, OlympiadBench), demonstrating that small, efficient models tuned with RL can match or exceed larger baselines on reasoning tasks.
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    Teammately

    Teammately

    Teammately

    Teammately is an autonomous AI agent designed to revolutionize AI development by self-iterating AI products, models, and agents to meet your objectives beyond human capabilities. It employs a scientific approach, refining and selecting optimal combinations of prompts, foundation models, and knowledge chunking. To ensure reliability, Teammately synthesizes fair test datasets and constructs dynamic LLM-as-a-judge systems tailored to your project, quantifying AI capabilities and minimizing hallucinations. The platform aligns with your goals through Product Requirement Docs (PRD), enabling focused iteration towards desired outcomes. Key features include multi-step prompting, serverless vector search, and deep iteration processes that continuously refine AI until objectives are achieved. Teammately also emphasizes efficiency by identifying the smallest viable models, reducing costs, and enhancing performance.
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    Superinterface

    Superinterface

    Superinterface

    Superinterface is an open source platform that enables seamless integration of AI-driven user interfaces into your products. It offers adaptable, headless UI options, allowing you to add in-app AI assistants with interactive components, API function calls, and voice chat capabilities. The platform supports various AI models, including those from OpenAI, Anthropic, and Mistral, providing flexibility in AI integration. Superinterface simplifies the process of embedding AI assistants into your website or application through methods like script tags, React components, or dedicated webpages, ensuring quick setup and compatibility with your existing technology stack. Customization features allow you to tailor the assistant's appearance to match your brand, including avatar selection, accent colors, and themes. Additionally, it supports functionalities such as file search, vector stores, and knowledge bases, enhancing the assistant's ability to provide relevant information.
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    Bria.ai

    Bria.ai

    Bria.ai

    Bria.ai is a powerful generative AI platform that specializes in creating and editing images at scale. It provides developers and enterprises with flexible solutions for AI-driven image generation, editing, and customization. Bria.ai offers APIs, iFrames, and pre-built models that allow users to integrate image creation and editing capabilities into their applications. The platform is designed for businesses seeking to enhance their branding, create marketing content, or automate product shot editing. With fully licensed data and customizable tools, Bria.ai ensures businesses can develop scalable, copyright-safe AI solutions.