40 Integrations with Together AI
View a list of Together AI integrations and software that integrates with Together AI below. Compare the best Together AI integrations as well as features, ratings, user reviews, and pricing of software that integrates with Together AI. Here are the current Together AI integrations in 2026:
-
1
ONLYOFFICE Docs
Ascensio System SIA
ONLYOFFICE is an open-source project that offers cloud-based and self-hosted solutions for business of all sizes. The key product is ONLYOFFICE Docs, a secure office suite that seamlessly integrates into the most popular platforms, e.g. Odoo, Alfresco, Confluence, Pipedrive, Redmine, SuiteCRM and more. When integrated, ONLYOFFICE Docs provides the users of your business app with editors for documents, spreadsheets, presentations, forms, PDFs and diagrams. The ONLYOFFICE suite makes it possible to collaborate on office files in real time. The built-in AI assistant is compatible with ChatGPT, DeepSeek, Mistral and other AI providers to ensure a flawless editing experience. You can use Docs within ONLYOFFICE DocSpace, a room-based document collaboration platform that allows you to create dedicated spaces where you can assign access permissions and collaborate with your teammates. With DocSpace, you can store, share and co-edit office files, and even interact with third parties.Starting Price: Free -
2
StackAI
StackAI
StackAI is an enterprise AI automation platform to build end-to-end internal tools and processes with AI agents in a fully compliant and secure way. Designed for large, regulated organizations, it enables teams to automate complex workflows across operations, compliance, finance, IT, and support without heavy engineering. With StackAI you can: • Connect knowledge bases (SharePoint, Confluence, Notion, Google Drive, databases) with versioning, citations, and access controls • Publish AI agents as chat assistants, advanced forms, or APIs integrated into Slack, Teams, Salesforce, HubSpot, or ServiceNow • Govern usage with enterprise security: SSO (Okta, Azure AD, Google), RBAC, audit logs, PII masking, data residency, and cost controls • Route across OpenAI, Anthropic, Google, or local LLMs with guardrails, evaluations, and testing • Deploy in multi-tenant cloud, dedicated cloud, private cloud, or on-premiseStarting Price: $0 -
3
Kimi K2.7 Code
Moonshot AI
Kimi K2.7 Code is an open-source, coding-focused agentic AI model developed by Moonshot AI for long-horizon software engineering tasks. It is designed to improve coding performance, agent workflows, and real-world development assistance compared with earlier Kimi K2 versions. The model supports a 256K context window, making it useful for working with large codebases, long technical documents, and complex multi-step programming tasks. Kimi K2.7 Code is available through Kimi Code and API access, with OpenAI- and Anthropic-compatible options for easier integration into developer workflows. It is also listed on Hugging Face and supports deployment through inference engines such as vLLM, SGLang, and KTransformers. With improved agentic capabilities, long-context support, and reduced thinking-token usage compared with K2.6, Kimi K2.7 Code gives developers a flexible open-source option for AI-assisted coding.Starting Price: Free -
4
GLM-5.2
Zhipu AI
GLM-5.2 is an advanced AI foundation model designed to support complex reasoning, coding, and long-range agentic tasks. It helps developers, teams, and organizations build intelligent systems that can understand instructions, solve technical problems, and assist with demanding workflows. The model is especially useful for software engineering, automation, research, and productivity-focused applications. GLM-5.2 is built to handle large amounts of context, making it suitable for projects that require deeper understanding across extended conversations, documents, or codebases. Its mixture-of-experts design helps balance strong performance with more efficient model operation. GLM-5.2 gives businesses and developers a powerful AI tool for creating smarter applications, improving technical workflows, and supporting advanced digital experiences.Starting Price: Free -
5
Kimi K2.5
Moonshot AI
Kimi K2.5 is a next-generation multimodal AI model designed for advanced reasoning, coding, and visual understanding tasks. It features a native multimodal architecture that supports both text and visual inputs, enabling image and video comprehension alongside natural language processing. Kimi K2.5 delivers open-source state-of-the-art performance in agent workflows, software development, and general intelligence tasks. The model offers ultra-long context support with a 256K token window, making it suitable for large documents and complex conversations. It includes long-thinking capabilities that allow multi-step reasoning and tool invocation for solving challenging problems. Kimi K2.5 is fully compatible with the OpenAI API format, allowing developers to switch seamlessly with minimal changes. With strong performance, flexibility, and developer-focused tooling, Kimi K2.5 is built for production-grade AI applications.Starting Price: Free -
6
GLM-5.1
Zhipu AI
GLM-5.1 is the latest iteration of Z.ai’s GLM series, designed as a frontier-level, agent-oriented AI model optimized for coding, reasoning, and long-horizon workflows. It builds on the GLM-5 architecture, which uses a Mixture-of-Experts (MoE) design to deliver high performance while keeping inference costs efficient, and is part of a broader push toward open-weight, developer-accessible models. A core focus of GLM-5.1 is enabling agentic behavior, meaning it can plan, execute, and iterate across multi-step tasks rather than simply responding to single prompts. It is specifically designed to handle complex workflows such as debugging code, navigating repositories, and executing chained operations with sustained context. Compared to earlier models, GLM-5.1 improves reliability in long interactions, maintaining coherence across extended sessions and reducing breakdowns in multi-step reasoning.Starting Price: Free -
7
Kimi K2.6
Moonshot AI
Kimi K2.6 is a next-generation agentic AI model developed by Moonshot AI, designed to push forward real-world execution, coding, and multi-step reasoning beyond earlier K2 and K2.5 versions. It builds on a Mixture-of-Experts architecture and the multimodal, agent-first foundation of the Kimi series, combining language understanding, coding, and tool use into a single system capable of planning and executing complex workflows. It introduces deeper reasoning capabilities and significantly improved agent planning, allowing it to break down tasks, coordinate tools, and handle multi-file or multi-step problems with greater accuracy and efficiency. It supports advanced tool calling with high reliability, enabling integration with external systems such as web search or APIs, and includes built-in validation mechanisms to ensure correct execution formats.Starting Price: Free -
8
MiniMax M3
MiniMax
MiniMax M3 is an open-weight multimodal AI model designed for coding, agentic workflows, long-context reasoning, and complex automation tasks. The model combines frontier-level coding performance, native multimodal understanding, and a context window of up to 1 million tokens. MiniMax M3 uses MiniMax Sparse Attention to improve long-context efficiency while reducing compute requirements for large-scale inputs. It supports text, image, and video understanding, making it useful for workflows that combine code, documents, visual references, and tool-driven tasks. The model is built for repository-scale reasoning, software engineering, autonomous task execution, tool calling, and multi-step agent workflows. MiniMax M3 helps developers, AI teams, and enterprises build capable agents that can reason across large contexts and work with multimodal information.Starting Price: Free -
9
Langtail
Langtail
Langtail is a cloud-based application development tool designed to help companies debug, test, deploy, and monitor LLM-powered apps with ease. The platform offers a no-code playground for debugging prompts, fine-tuning model parameters, and running LLM tests to prevent issues when models or prompts change. Langtail specializes in LLM testing, including chatbot testing and ensuring robust AI LLM test prompts. With its comprehensive features, Langtail enables teams to: • Test LLM models thoroughly to catch potential issues before they affect production environments. • Deploy prompts as API endpoints for seamless integration. • Monitor model performance in production to ensure consistent outcomes. • Use advanced AI firewall capabilities to safeguard and control AI interactions. Langtail is the ideal solution for teams looking to ensure the quality, stability, and security of their LLM and AI-powered applications.Starting Price: $99/month/unlimited users -
10
Unify AI
Unify AI
Explore the power of choosing the right LLM for your needs and how to optimize for quality, speed, and cost-efficiency. Access all LLMs across all providers with a single API key and a standard API. Setup your own cost, latency, and output speed constraints. Define a custom quality metric. Personalize your router for your requirements. Systematically send your queries to the fastest provider, based on the very latest benchmark data for your region of the world, refreshed every 10 minutes. Get started with Unify with our dedicated walkthrough. Discover the features you already have access to and our upcoming roadmap. Just create a Unify account to access all models from all supported providers with a single API key. Our router balances output quality, speed, and cost based on user-specific preferences. The quality is predicted ahead of time using a neural scoring function, which predicts how good each model would be at responding to a given prompt.Starting Price: $1 per credit -
11
LlamaCoder
LlamaCoder
An open source tool to generate small apps with one prompt. Powered by Llama 3 405B & Together.ai.Starting Price: Free -
12
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.Starting Price: $249 per month -
13
E2B
E2B
E2B is an open source runtime designed to securely execute AI-generated code within isolated cloud sandboxes. It enables developers to integrate code interpretation capabilities into their AI applications and agents, facilitating the execution of dynamic code snippets in a controlled environment. The platform supports multiple programming languages, including Python and JavaScript, and offers SDKs for seamless integration. E2B utilizes Firecracker microVMs to ensure robust security and isolation for code execution. Developers can deploy E2B within their own infrastructure or utilize the provided cloud service. The platform is designed to be LLM-agnostic, allowing compatibility with various large language models such as OpenAI, Llama, Anthropic, and Mistral. E2B's features include rapid sandbox initialization, customizable execution environments, and support for long-running sessions up to 24 hours.Starting Price: Free -
14
LiteLLM
LiteLLM
LiteLLM is a versatile platform designed to streamline interactions with over 100 Large Language Models (LLMs) through a unified interface. It offers both a Proxy Server (LLM Gateway) and a Python SDK, enabling developers to integrate various LLMs seamlessly into their applications. The Proxy Server facilitates centralized management, allowing for load balancing, cost tracking across projects, and consistent input/output formatting compatible with OpenAI standards. This setup supports multiple providers. It ensures robust observability by generating unique call IDs for each request, aiding in precise tracking and logging across systems. Developers can leverage pre-defined callbacks to log data using various tools. For enterprise users, LiteLLM offers advanced features like Single Sign-On (SSO), user management, and professional support through dedicated channels like Discord and Slack.Starting Price: Free -
15
LangDB
LangDB
LangDB offers a community-driven, open-access repository focused on natural language processing tasks and datasets for multiple languages. It serves as a central resource for tracking benchmarks, sharing tools, and supporting the development of multilingual AI models with an emphasis on openness and cross-linguistic representation.Starting Price: $49 per month -
16
LLM Gateway
LLM Gateway
LLM Gateway is a fully open source, unified API gateway that lets you route, manage, and analyze requests to any large language model provider, OpenAI, Anthropic, Gemini Enterprise Agent Platform, and more, using a single, OpenAI-compatible endpoint. It offers multi-provider support with seamless migration and integration, dynamic model orchestration that routes each request to the optimal engine, and comprehensive usage analytics to track requests, token consumption, response times, and costs in real time. Built-in performance monitoring lets you compare models’ accuracy and cost-effectiveness, while secure key management centralizes API credentials under role-based controls. You can deploy LLM Gateway on your own infrastructure under the MIT license or use the hosted service as a progressive web app, and simple integration means you only need to change your API base URL, your existing code in any language or framework (cURL, Python, TypeScript, Go, etc.)Starting Price: $50 per month -
17
Qwen3-Coder
Qwen
Qwen3‑Coder is an agentic code model available in multiple sizes, led by the 480B‑parameter Mixture‑of‑Experts variant (35B active) that natively supports 256K‑token contexts (extendable to 1M) and achieves state‑of‑the‑art results comparable to Claude Sonnet 4. Pre‑training on 7.5T tokens (70 % code) and synthetic data cleaned via Qwen2.5‑Coder optimized both coding proficiency and general abilities, while post‑training employs large‑scale, execution‑driven reinforcement learning, scaling test‑case generation for diverse coding challenges, and long‑horizon RL across 20,000 parallel environments to excel on multi‑turn software‑engineering benchmarks like SWE‑Bench Verified without test‑time scaling. Alongside the model, the open source Qwen Code CLI (forked from Gemini Code) unleashes Qwen3‑Coder in agentic workflows with customized prompts, function calling protocols, and seamless integration with Node.js, OpenAI SDKs, and environment variables.Starting Price: Free -
18
Metorial
Metorial
Metorial is an open source, developer-centric integration platform that streamlines the creation, deployment, monitoring, and scaling of agentic AI applications by connecting models to tools, data, and APIs via the Model Context Protocol. With a catalog of over 600 verified MCP “servers,” developers can give their agents capabilities like interacting with Slack, Google Calendar, Notion, APIs, databases, or other systems in just a few clicks or one API call. Metorial’s infrastructure is serverless and built for scale, deploying MCP servers in three clicks or an API call, supporting “zero to millions” of requests, and offering out-of-the-box observability including detailed logging, tracing, session replay, and error alerts. A full set of SDKs (Python, TypeScript) is provided, and every interaction is traceable so teams can audit and optimize agent behaviour. Whether self-hosted or cloud-powered, Metorial offers enterprise-grade security and multi-tenant support.Starting Price: $35 per month -
19
Rebolt.ai
Rebolt.ai
Rebolt is an enterprise-grade AI platform that empowers companies to build custom applications and intelligent agents simply by speaking with AI. The platform integrates seamlessly with corporate tools such as OneDrive, SharePoint, Salesforce, Slack, and custom APIs, offering built-in infrastructure like databases, file storage, scheduling (cron jobs), audit logs, and distinct staging and production environments for deployment. Users can create apps and agents without writing API key code by simply describing what they need in natural language, while maintaining enterprise-class security, permissions mapping (e.g., via Azure groups), and role-based access. Rebolt is designed for building operational workflows, internal tools, and automation that connect to existing company data and services, enabling non-technical users (or low-code teams) to rapidly assemble solutions and replace spreadsheets, manual processes, and fragmented SaaS stacks.Starting Price: $25 per month -
20
DeepCoder
Agentica Project
DeepCoder is a fully open source code-reasoning and generation model released by Agentica Project in collaboration with Together AI. It is fine-tuned from DeepSeek-R1-Distilled-Qwen-14B using distributed reinforcement learning, achieving a 60.6% accuracy on LiveCodeBench (representing an 8% improvement over the base), a performance level that matches that of proprietary models such as o3-mini (2025-01-031 Low) and o1 while using only 14 billion parameters. It was trained over 2.5 weeks on 32 H100 GPUs with a curated dataset of roughly 24,000 coding problems drawn from verified sources (including TACO-Verified, PrimeIntellect SYNTHETIC-1, and LiveCodeBench submissions), each problem requiring a verifiable solution and at least five unit tests to ensure reliability for RL training. To handle long-range context, DeepCoder employs techniques such as iterative context lengthening and overlong filtering.Starting Price: Free -
21
DeepSWE
Agentica Project
DeepSWE is a fully open source, state-of-the-art coding agent built on top of the Qwen3-32B foundation model and trained exclusively via reinforcement learning (RL), without supervised finetuning or distillation from proprietary models. It is developed using rLLM, Agentica’s open source RL framework for language agents. DeepSWE operates as an agent; it interacts with a simulated development environment (via the R2E-Gym environment) using a suite of tools (file editor, search, shell-execution, submit/finish), enabling it to navigate codebases, edit multiple files, compile/run tests, and iteratively produce patches or complete engineering tasks. DeepSWE exhibits emergent behaviors beyond simple code generation; when presented with bugs or feature requests, the agent reasons about edge cases, seeks existing tests in the repository, proposes patches, writes extra tests for regressions, and dynamically adjusts its “thinking” effort.Starting Price: Free -
22
DeepSeek-V4
DeepSeek
DeepSeek-V4 is a next-generation open-source language model designed for high-performance reasoning, coding, and long-context intelligence. It introduces a powerful architecture with up to one million token context length, enabling seamless handling of large datasets and complex multi-step workflows. The model comes in two variants: DeepSeek-V4-Pro for maximum performance and DeepSeek-V4-Flash for efficiency and speed. DeepSeek-V4-Pro features 1.6 trillion total parameters with 49 billion activated, delivering near state-of-the-art performance comparable to leading closed-source models. It excels in agentic coding, mathematical reasoning, and world knowledge tasks. The model integrates advanced attention mechanisms, including token-wise compression and sparse attention, significantly reducing compute and memory costs. It is also optimized for AI agents, supporting tool use and multi-step workflows.Starting Price: Free -
23
Qwen3.5
Alibaba
Qwen3.5 is a next-generation open-weight multimodal large language model designed to power native vision-language agents. The flagship release, Qwen3.5-397B-A17B, combines a hybrid linear attention architecture with sparse mixture-of-experts, activating only 17 billion parameters per forward pass out of 397 billion total to maximize efficiency. It delivers strong benchmark performance across reasoning, coding, multilingual understanding, visual reasoning, and agent-based tasks. The model expands language support from 119 to 201 languages and dialects while introducing a 1M-token context window in its hosted version, Qwen3.5-Plus. Built for multimodal tasks, it processes text, images, and video with advanced spatial reasoning and tool integration. Qwen3.5 also incorporates scalable reinforcement learning environments to improve general agent capabilities. Designed for developers and enterprises, it enables efficient, tool-augmented, multimodal AI workflows.Starting Price: Free -
24
MiniMax M2.7
MiniMax
MiniMax M2.7 is an advanced AI model designed to enhance real-world productivity across coding, search, and office workflows. It is trained with reinforcement learning across numerous real-world environments, enabling it to handle complex, multi-step tasks effectively. The model excels in problem-solving by breaking down challenges before generating solutions across multiple programming languages. It delivers high-speed performance with rapid token generation, allowing tasks to be completed efficiently. With optimized reasoning and cost-effective pricing, it provides powerful capabilities while minimizing resource usage. It also achieves strong performance in software engineering benchmarks, reducing incident response time and improving development efficiency. Additionally, it supports advanced agentic workflows and professional-grade office tasks, making it highly versatile for modern work environments.Starting Price: Free -
25
DeepSeek-V4-Pro
DeepSeek
DeepSeek-V4-Pro is a large-scale Mixture-of-Experts (MoE) language model designed for advanced reasoning, coding, and long-context understanding. It features 1.6 trillion total parameters with 49 billion activated parameters, enabling high performance while maintaining efficiency. The model supports an exceptionally large context window of up to one million tokens, allowing it to process extensive documents and workflows. It uses a hybrid attention architecture to optimize long-context performance and reduce computational cost. DeepSeek-V4-Pro is trained on over 32 trillion tokens, improving its knowledge and reasoning capabilities. It also includes advanced optimization techniques for stability and faster convergence during training. The model supports multiple reasoning modes, allowing users to balance speed and accuracy based on their needs. Overall, it provides a powerful open-source solution for complex AI tasks and large-scale applications.Starting Price: Free -
26
DeepSeek-V4-Flash
DeepSeek
DeepSeek-V4-Flash is a high-efficiency Mixture-of-Experts (MoE) language model designed for fast, scalable reasoning and text generation. It features 284 billion total parameters with 13 billion activated parameters, delivering strong performance while optimizing computational cost. The model supports an extensive context window of up to one million tokens, enabling it to process large documents and complex workflows with ease. Its hybrid attention architecture enhances long-context efficiency by reducing memory and compute requirements. Trained on over 32 trillion tokens, DeepSeek-V4-Flash demonstrates solid capabilities across knowledge, reasoning, and coding tasks. It is designed for scenarios where speed and efficiency are critical, offering a balance between performance and resource usage. The model also supports multiple reasoning modes, allowing users to adjust between faster outputs and deeper analysis.Starting Price: Free -
27
OllaCoder
OllaCoder
OllaCoder is a private AI coding assistant for VS Code, built for engineers who refuse to ship their source code to someone else’s server. It runs locally, works with your own Ollama models, and brings agent mode, inline edits, codebase chat, smart autocomplete, MCP servers, and a local-first runtime into one editor. OllaCoder is built on the idea that software is a private craft: your code should stay yours, and an AI assistant should be powerful, honest, and silent. By default, it talks to your local Ollama instance, so prompts, completions, and edits stay on your computer; cloud providers are strictly opt-in, and API keys live encrypted in the OS keychain. Its agent mode can plan tasks, edit files, run the terminal, and verify its own work, with every step available for approval, denial, or rollback. Inline edits let users highlight a function, describe the change, and review a real diff hunk by hunk.Starting Price: Free -
28
RapidClaims
RapidClaims
Reduce administrative costs and improve reimbursements, all while maintaining compliance. Supercharge your RCM process with RapidClaims AI-driven magic. Slash admin costs, boost reimbursements, and stay compliant effortlessly. Streamline your coding process, and automate or empower your coders with our personalized solutions. Code thousands of charts with speed and precision while catering to unique client requirements. Our Large language model can interpret unstructured data, creating a longitudinal patient record by converting notes into structured codes and disease patterns. Never make the same mistakes twice. Create mass-level coding-related rules with plain English and easily apply them to your charts at scale, segregated by specialty, code type, and coders. Gain a deeper understanding of code-level trends for different sites and take action to improve the revenue cycle. Our platform analyzes charts to identify claim denial patterns and helps you capture them. -
29
HoneyHive
HoneyHive
AI engineering doesn't have to be a black box. Get full visibility with tools for tracing, evaluation, prompt management, and more. HoneyHive is an AI observability and evaluation platform designed to assist teams in building reliable generative AI applications. It offers tools for evaluating, testing, and monitoring AI models, enabling engineers, product managers, and domain experts to collaborate effectively. Measure quality over large test suites to identify improvements and regressions with each iteration. Track usage, feedback, and quality at scale, facilitating the identification of issues and driving continuous improvements. HoneyHive supports integration with various model providers and frameworks, offering flexibility and scalability to meet diverse organizational needs. It is suitable for teams aiming to ensure the quality and performance of their AI agents, providing a unified platform for evaluation, monitoring, and prompt management. -
30
Nurix
Nurix
Nurix AI is a Bengaluru-based company specializing in the development of custom AI agents designed to automate and enhance enterprise workflows across various sectors, including sales and customer support. Nurix AI's platform integrates seamlessly with existing enterprise systems, enabling AI agents to execute complex tasks autonomously, provide real-time responses, and make intelligent decisions without constant human oversight. A standout feature is their proprietary voice-to-voice model, which supports low-latency, human-like conversations in multiple languages, enhancing customer interactions. Nurix AI offers tailored AI services for startups, providing end-to-end solutions to build and scale AI products without the need for extensive in-house teams. Their expertise encompasses large language models, cloud integration, inference, and model training, ensuring that clients receive reliable and enterprise-ready AI solutions. -
31
Assembly
Factory.ai
Assembly brings your entire development context into focus, starting each day with clarity. It is designed to revolutionize software development by integrating understanding, planning, coding, reviewing, and documentation into a cohesive system. Serving as the command center for development teams, Factory offers personalized dashboards that highlight relevant tasks and streamline workflows, ensuring clarity and efficiency from the start of each day. The platform facilitates collaborative design and planning, allowing teams to craft architectures, draft requirements, and outline technical roadmaps with ease. Its codebase Q&A feature accelerates onboarding and knowledge sharing by capturing context and decisions, simplifying the comprehension of complex systems. Factory's AI-driven code review system delves deep into codebases, identifying subtle issues and assisting in implementing feedback effectively.Starting Price: $80 per month -
32
RouteLLM
LMSYS
Developed by LM-SYS, RouteLLM is an open-source toolkit that allows users to route tasks between different large language models to improve efficiency and manage resources. It supports strategy-based routing, helping developers balance speed, accuracy, and cost by selecting the best model for each input dynamically. -
33
Orq.ai
Orq.ai
Orq.ai is the #1 platform for software teams to operate agentic AI systems at scale. Optimize prompts, deploy use cases, and monitor performance, no blind spots, no vibe checks. Experiment with prompts and LLM configurations before moving to production. Evaluate agentic AI systems in offline environments. Roll out GenAI features to specific user groups with guardrails, data privacy safeguards, and advanced RAG pipelines. Visualize all events triggered by agents for fast debugging. Get granular control on cost, latency, and performance. Connect to your favorite AI models, or bring your own. Speed up your workflow with out-of-the-box components built for agentic AI systems. Manage core stages of the LLM app lifecycle in one central platform. Self-hosted or hybrid deployment with SOC 2 and GDPR compliance for enterprise security. -
34
Vertesia
Vertesia
Vertesia is a unified, low-code generative AI platform that enables enterprise teams to rapidly build, deploy, and operate GenAI applications and agents at scale. Designed for both business professionals and IT specialists, Vertesia offers a frictionless development experience, allowing users to go from prototype to production without extensive timelines or heavy infrastructure. It supports multiple generative AI models from leading inference providers, providing flexibility and preventing vendor lock-in. Vertesia's agentic retrieval-augmented generation (RAG) pipeline enhances generative AI accuracy and performance by automating and accelerating content preparation, including intelligent document processing and semantic chunking. With enterprise-grade security, SOC2 compliance, and support for leading cloud infrastructures like AWS, GCP, and Azure, Vertesia ensures secure and scalable deployments. -
35
LFM2
Liquid AI
LFM2 is a next-generation series of on-device foundation models built to deliver the fastest generative-AI experience across a wide range of endpoints. It employs a new hybrid architecture that achieves up to 2x faster decode and prefill performance than comparable models, and up to 3x improvements in training efficiency compared to the previous generation. These models strike an optimal balance of quality, latency, and memory for deployment on embedded systems, allowing real-time, on-device AI across smartphones, laptops, vehicles, wearables, and other endpoints, enabling millisecond inference, device resilience, and full data sovereignty. Available in three dense checkpoints (0.35 B, 0.7 B, and 1.2 B parameters), LFM2 demonstrates benchmark performance that outperforms similarly sized models in tasks such as knowledge recall, mathematics, multilingual instruction-following, and conversational dialogue evaluations. -
36
Continue
Continue
The leading open-source AI code assistant. You can connect any models and any context to create custom autocomplete and chat experiences inside the IDE Remain in flow while coding by removing the barriers that block productivity when building software. Accelerate development with a plug-and-play system that makes it easy to get started and integrates with your entire stack. Become a leader in AI by setting up your code assistant to evolve as new capabilities emerge. Continue autocompletes single lines or entire sections of code in any programming language as you type. Attach code or other context to ask questions about functions, files, the entire codebase, and more. Highlight code sections and press a keyboard shortcut to rewrite code from natural language.Starting Price: $0/developer/month -
37
gpt-oss-20b
OpenAI
gpt-oss-20b is a 20-billion-parameter, text-only reasoning model released under the Apache 2.0 license and governed by OpenAI’s gpt-oss usage policy, built to enable seamless integration into custom AI workflows via the Responses API without reliance on proprietary infrastructure. Trained for robust instruction following, it supports adjustable reasoning effort, full chain-of-thought outputs, and native tool use (including web search and Python execution), producing structured, explainable answers. Developers must implement their own deployment safeguards, such as input filtering, output monitoring, and usage policies, to match the system-level protections of hosted offerings and mitigate risks from malicious or unintended behaviors. Its open-weight design makes it ideal for on-premises or edge deployments where control, customization, and transparency are paramount. -
38
gpt-oss-120b
OpenAI
gpt-oss-120b is a reasoning model engineered for deep, transparent thinking, delivering full chain-of-thought explanations, adjustable reasoning depth, and structured outputs, while natively invoking tools like web search and Python execution via the API. Built to slot seamlessly into self-hosted or edge deployments, it eliminates dependence on proprietary infrastructure. Although it includes default safety guardrails, its open-weight architecture allows fine-tuning that could override built-in controls, so implementers are responsible for adding input filtering, output monitoring, and governance measures to achieve enterprise-grade security. As a community–driven model card rather than a managed service spec, it emphasizes transparency, customization, and the need for downstream safety practices. -
39
Wan2.6
Alibaba
Wan 2.6 is Alibaba’s advanced multimodal video generation model designed to create high-quality, audio-synchronized videos from text or images. It supports video creation up to 15 seconds in length while maintaining strong narrative flow and visual consistency. The model delivers smooth, realistic motion with cinematic camera movement and pacing. Native audio-visual synchronization ensures dialogue, sound effects, and background music align perfectly with visuals. Wan 2.6 includes precise lip-sync technology for natural mouth movements. It supports multiple resolutions, including 480p, 720p, and 1080p. Wan 2.6 is well-suited for creating short-form video content across social media platforms.Starting Price: Free -
40
Nemotron 3 Super
NVIDIA
Nemotron-3 Super is part of NVIDIA’s Nemotron 3 family of open models designed to enable advanced agentic AI systems that can reason, plan, and execute multi-step workflows across complex environments. The model introduces a hybrid Mamba-Transformer Mixture-of-Experts architecture that combines the efficiency of state-space Mamba layers with the contextual understanding of transformer attention, allowing it to process long sequences and complex reasoning tasks with high accuracy and throughput. This architecture activates only a subset of model parameters for each token, improving computational efficiency while maintaining strong reasoning capabilities and enabling scalable inference for large workloads. Nemotron-3 Super contains roughly 120 billion parameters with around 12 billion active during inference, accelerating multi-step reasoning and collaborative agent interactions across large contexts.
- Previous
- You're on page 1
- Next
