Best AI Models in the USA - Page 14
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Compare the Top AI Models in the USA as of February 2026 - Page 14
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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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Gemini 2.5 Flash-Lite
Google
Gemini 2.5 is Google DeepMind’s latest generation AI model family, designed to deliver advanced reasoning and native multimodality with a long context window. It improves performance and accuracy by reasoning through its thoughts before responding. The model offers different versions tailored for complex coding tasks, fast everyday performance, and cost-efficient high-volume workloads. Gemini 2.5 supports multiple data types including text, images, video, audio, and PDFs, enabling versatile AI applications. It features adaptive thinking budgets and fine-grained control for developers to balance cost and output quality. Available via Google AI Studio and Gemini API, Gemini 2.5 powers next-generation AI experiences. -
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Mu
Microsoft
Mu is a 330-million-parameter encoder–decoder language model designed to power the agent in Windows settings by mapping natural-language queries to Settings function calls, running fully on-device via NPUs at over 100 tokens per second while maintaining high accuracy. Drawing on Phi Silica optimizations, Mu’s encoder–decoder architecture reuses a fixed-length latent representation to cut computation and memory overhead, yielding 47 percent lower first-token latency and 4.7× higher decoding speed on Qualcomm Hexagon NPUs compared to similar decoder-only models. Hardware-aware tuning, including a 2/3–1/3 encoder–decoder parameter split, weight sharing between input and output embeddings, Dual LayerNorm, rotary positional embeddings, and grouped-query attention, enables fast inference at over 200 tokens per second on devices like Surface Laptop 7 and sub-500 ms response times for settings queries. -
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Gemini Robotics
Google DeepMind
Gemini Robotics brings Gemini’s capacity for multimodal reasoning and world understanding into the physical world, allowing robots of any shape and size to perform a wide range of real-world tasks. Built on Gemini 2.0, it augments advanced vision-language-action models with the ability to reason about physical spaces, generalize to novel situations, including unseen objects, diverse instructions, and new environments, and understand and respond to everyday conversational commands while adapting to sudden changes in instructions or surroundings without further input. Its dexterity module enables complex tasks requiring fine motor skills and precise manipulation, such as folding origami, packing lunch boxes, or preparing salads, and it supports multiple embodiments, from bi-arm platforms like ALOHA 2 to humanoid robots such as Apptronik’s Apollo. It is optimized for local execution and has an SDK for seamless adaptation to new tasks and environments. -
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Grok 4 Heavy
xAI
Grok 4 Heavy is the most powerful AI model offered by xAI, designed as a multi-agent system to deliver cutting-edge reasoning and intelligence. Built on the Colossus supercomputer, it achieves a 50% score on the challenging HLE benchmark, outperforming many competitors. This advanced model supports multimodal inputs including text and images, with plans to add video capabilities. Grok 4 Heavy targets power users such as developers, researchers, and technical enthusiasts who require top-tier AI performance. Access is provided through the premium “SuperGrok Heavy” subscription priced at $300 per month. xAI has enhanced moderation and removed problematic system prompts to ensure responsible and ethical AI use. -
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Phi-4-mini-flash-reasoning
Microsoft
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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Voxtral
Mistral AI
Voxtral models are frontier open source speech‑understanding systems available in two sizes—a 24 B variant for production‑scale applications and a 3 B variant for local and edge deployments, both released under the Apache 2.0 license. They combine high‑accuracy transcription with native semantic understanding, supporting long‑form context (up to 32 K tokens), built‑in Q&A and structured summarization, automatic language detection across major languages, and direct function‑calling to trigger backend workflows from voice. Retaining the text capabilities of their Mistral Small 3.1 backbone, Voxtral handles audio up to 30 minutes for transcription or 40 minutes for understanding and outperforms leading open source and proprietary models on benchmarks such as LibriSpeech, Mozilla Common Voice, and FLEURS. Accessible via download on Hugging Face, API endpoint, or private on‑premises deployment, Voxtral also offers domain‑specific fine‑tuning and advanced enterprise features. -
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AudioLM
Google
AudioLM is a pure audio language model that generates high‑fidelity, long‑term coherent speech and piano music by learning from raw audio alone, without requiring any text transcripts or symbolic representations. It represents audio hierarchically using two types of discrete tokens, semantic tokens extracted from a self‑supervised model to capture phonetic or melodic structure and global context, and acoustic tokens from a neural codec to preserve speaker characteristics and fine waveform details, and chains three Transformer stages to predict first semantic tokens for high‑level structure, then coarse and finally fine acoustic tokens for detailed synthesis. The resulting pipeline allows AudioLM to condition on a few seconds of input audio and produce seamless continuations that retain voice identity, prosody, and recording conditions in speech or melody, harmony, and rhythm in music. Human evaluations show that synthetic continuations are nearly indistinguishable from real recordings. -
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GLM-4.5
Z.ai
GLM‑4.5 is Z.ai’s latest flagship model in the GLM family, engineered with 355 billion total parameters (32 billion active) and a companion GLM‑4.5‑Air variant (106 billion total, 12 billion active) to unify advanced reasoning, coding, and agentic capabilities in one architecture. It operates in a “thinking” mode for complex, multi‑step reasoning and tool use, and a “non‑thinking” mode for instant responses, supporting up to 128 K token context length and native function calling. Available via the Z.ai chat platform and API, with open weights on HuggingFace and ModelScope, GLM‑4.5 ingests diverse inputs to solve general problem‑solving, common‑sense reasoning, coding from scratch or within existing projects, and end‑to‑end agent workflows such as web browsing and slide generation. Built on a Mixture‑of‑Experts design with loss‑free balance routing, grouped‑query attention, and an MTP layer for speculative decoding, it delivers enterprise‑grade performance. -
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Harmonic Aristotle
Harmonic
Aristotle is the first AI model built from the ground up as a Mathematical Superintelligence (MSI), designed to deliver provably correct solutions to complex quantitative problems without hallucinations. When prompted with natural‑language math questions, it formalizes them in Lean 4, solves them via formally verified proofs, and returns both the proof and a natural‑language explanation. Unlike conventional language models that rely on probabilistic outputs, Aristotle’s MSI architecture replaces guesswork with provable logic, transparently flagging any errors or inconsistencies. The AI is accessible through a web interface and a developer API, enabling researchers to integrate its rigorous reasoning into workflows across fields such as theoretical physics, engineering, and computer science. -
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Runway Aleph
Runway
Runway Aleph is a state‑of‑the‑art in‑context video model that redefines multi‑task visual generation and editing by enabling a vast array of transformations on any input clip. It can seamlessly add, remove, or transform objects within a scene, generate new camera angles, and adjust style and lighting, all guided by natural‑language instructions or visual prompts. Built on cutting‑edge deep‑learning architectures and trained on diverse video datasets, Aleph operates entirely in context, understanding spatial and temporal relationships to maintain realism across edits. Users can apply complex effects, such as object insertion, background replacement, dynamic relighting, and style transfers, without needing separate tools for each task. The model’s intuitive interface integrates directly into Runway’s existing Gen‑4 ecosystem, offering an API for developers and a visual workspace for creators. -
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AlphaEarth Foundations
Google DeepMind
AlphaEarth Foundations is a new AI model from DeepMind that acts like a “virtual satellite” by integrating massive, heterogeneous Earth observation data, optical and radar imagery, 3D laser mapping, climate simulations, and more, into a unified, highly compact embedding for land and coastal areas, enabling consistent, on-demand planetary-scale mapping with far less storage overhead than prior systems. It fuses disparate streams to solve data overload and inconsistency, producing summaries that are 16 times smaller than comparable methods while delivering better accuracy (about 24% lower error in tested tasks) even where labeled data is sparse. Annual embedding collections are published as the satellite embedding dataset in Google Earth Engine and are already being applied by institutions to classify unmapped ecosystems, monitor agricultural and environmental change. -
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Command A Vision
Cohere AI
Command A Vision is Cohere’s multimodal AI solution built for enterprise use that combines image understanding with language capabilities to drive business outcomes while keeping compute costs low; it extends the Command family by adding vision comprehension, allowing organizations to interpret and act on visual content in concert with text, and integrates into workplace systems to surface insights, boost productivity, and enable more intelligent search and discovery. The offering is positioned alongside Cohere’s broader AI stack and emphasizes putting AI to work in real-world workflows, helping teams unify multimodal signals, extract actionable meaning from images and associated metadata, and surface relevant business intelligence without excessive infrastructure overhead. Command A Vision excels at understanding and analyzing a wide range of visual and multilingual data, including charts, graphs, tables, and diagrams. -
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Gemini 2.5 Deep Think
Google
Gemini 2.5 Deep Think is an enhanced reasoning mode within the Gemini 2.5 family that uses extended, parallel thinking and novel reinforcement learning techniques to tackle complex, multi-step problems in areas like math, coding, science, and strategic planning by generating and evaluating multiple lines of thought before responding, producing more detailed, creative, and accurate answers with support for longer replies and built-in tool integration (e.g., code execution and web search). Its performance shows state-of-the-art results on rigorous benchmarks, including LiveCodeBench V6 and Humanity’s Last Exam, and it demonstrates notable gains over previous versions in challenging domains, with internal evaluations also indicating improved content safety and tone-objectivity, though with a higher tendency to decline benign requests; Google is conducting frontier safety evaluations and implementing mitigations to manage risks as the model’s capabilities advance. -
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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. -
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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. -
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Claude Opus 4.1
Anthropic
Claude Opus 4.1 is an incremental upgrade to Claude Opus 4 that boosts coding, agentic reasoning, and data-analysis performance without changing deployment complexity. It raises coding accuracy to 74.5 percent on SWE-bench Verified and sharpens in-depth research and detailed tracking for agentic search tasks. GitHub reports notable gains in multi-file code refactoring, while Rakuten Group highlights its precision in pinpointing exact corrections within large codebases without introducing bugs. Independent benchmarks show about a one-standard-deviation improvement on junior developer tests compared to Opus 4, mirroring major leaps seen in prior Claude releases. Opus 4.1 is available now to paid Claude users, in Claude Code, and via the Anthropic API (model ID claude-opus-4-1-20250805), as well as through Amazon Bedrock and Google Cloud Vertex AI, and integrates seamlessly into existing workflows with no additional setup beyond selecting the new model. -
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GPT-5 pro
OpenAI
GPT-5 Pro is OpenAI’s most advanced AI model, designed to tackle the most complex and challenging tasks with extended reasoning capabilities. It builds on GPT-5’s unified architecture, using scaled, efficient parallel compute to provide highly comprehensive and accurate responses. GPT-5 Pro achieves state-of-the-art performance on difficult benchmarks like GPQA, excelling in areas such as health, science, math, and coding. It makes significantly fewer errors than earlier models and delivers responses that experts find more relevant and useful. The model automatically balances quick answers and deep thinking, allowing users to get expert-level insights efficiently. GPT-5 Pro is available to Pro subscribers and powers some of the most demanding applications requiring advanced intelligence. -
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GPT-5 thinking
OpenAI
GPT-5 Thinking is the deeper reasoning mode within the GPT-5 unified AI system, designed to tackle complex, open-ended problems that require extended cognitive effort. It works alongside the faster GPT-5 model, dynamically engaging when queries demand more detailed analysis and thoughtful responses. This mode significantly reduces hallucinations and improves factual accuracy, producing more reliable answers on challenging topics like science, math, coding, and health. GPT-5 Thinking is also better at recognizing its own limitations, communicating clearly when tasks are impossible or underspecified. It incorporates advanced safety features to minimize harmful outputs and provide nuanced, helpful answers even in ambiguous or sensitive contexts. Available to all users, it helps bring expert-level intelligence to everyday and advanced use cases alike. -
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Genie 3
Google DeepMind
Genie 3 is DeepMind’s next-generation, general-purpose world model capable of generating richly interactive 3D environments in real time at 24 frames per second and 720p resolution that remain consistent for several minutes. Prompted by text input, the system constructs dynamic virtual worlds where users (or embodied agents) can navigate and interact with natural phenomena from multiple perspectives, like first-person or isometric. A standout feature is its emergent long-horizon visual memory: Genie 3 maintains environmental consistency over extended durations, preserving off-screen elements and spatial coherence across revisits. It also supports “promptable world events,” enabling users to modify scenes, such as changing weather or introducing new objects, on the fly. Designed to support embodied agent research, Genie 3 seamlessly integrates with agents like SIMA, facilitating goal-based navigation and complex task accomplishment. -
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Mistral Medium 3.1
Mistral AI
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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Marble
World Labs
Marble is an experimental AI model internally tested by World Labs, a variant and extension of their Large World Model technology. It is a web service that turns a single 2D image into a navigable spatial environment. Marble offers two generation modes: a smaller, fast model for rough previews that’s quick to iterate on, and a larger, high-fidelity model that takes longer (around ten minutes in the example) but produces a significantly more convincing result. The value proposition is instant, photogrammetry-like image-to-world creation without a full capture rig, turning a single shot into an explorable space for memory capture, mood boards, archviz previews, or creative experiments. -
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Command A Reasoning
Cohere AI
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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MuseSteamer
Baidu
Baidu’s AI-powered video creation platform is built on its proprietary MuseSteamer model, enabling users to generate high-quality short videos from a single static image. Featuring a clean, intuitive interface, it supports smart generation of dynamic visuals, such as character micro-expressions and animated scenes, accompanied by sound via Chinese audio-video integrated generation. Users benefit from instant creative tools like inspiration recommendations and one-click style matching, selecting from a rich template library to effortlessly produce compelling visuals. It supplies refined editing capabilities, including multi-track timeline trimming, overlaying special effects, and AI-assisted voiceover, streamlining workflow from idea to polished output. Videos render rapidly, typically in mere minutes, making it ideal for quick production of social media content, promotional visuals, educational animations, and campaign assets with vivid motion and professional polish. -
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Mirage 2
Dynamics Lab
Mirage 2 is an AI-driven Generative World Engine that lets anyone instantly transform images or descriptions into fully playable, interactive game environments directly in the browser. Upload sketches, concept art, photos, or prompts, like “Ghibli-style village” or “Paris street scene”, and Mirage 2 builds immersive worlds you can explore in real time. The experience isn’t pre-scripted: you can modify your world mid-play using natural-language chat, evolving settings dynamically, from a cyberpunk city to a rainforest or a mountaintop castle, all with minimal latency (around 200 ms) on a single consumer GPU. Mirage 2 supports smooth rendering, real-time prompt control, and extended gameplay stretches beyond ten minutes. It outpaces earlier world-model systems by offering true general-domain generation, no upper limit on styles or genres, as well as seamless world adaptation and sharing features. -
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Nano Banana
Google
Nano Banana is Gemini’s fast, accessible image-creation model designed for quick, playful, and casual creativity. It lets users blend photos, maintain character consistency, and make small local edits with ease. The tool is perfect for transforming selfies, reimagining pictures with fun themes, or combining two images into one. With its ability to handle stylistic changes, it can turn photos into figurine-style designs, retro portraits, or aesthetic makeovers using simple prompts. Nano Banana makes creative experimentation easy and enjoyable, requiring no advanced skills or complex controls. It’s the ideal starting point for users who want simple, fast, and imaginative image editing inside the Gemini app. -
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Command A Translate
Cohere AI
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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MAI-1-preview
Microsoft
MAI-1 Preview is Microsoft AI’s first end-to-end trained foundation model, built entirely in-house as a mixture-of-experts architecture. Pre-trained and post-trained on approximately 15,000 NVIDIA H100 GPUs, it is designed to follow instructions and generate helpful, responsive text for everyday user queries, representing a prototype of future Copilot capabilities. Now available for public testing on LMArena, MAI-1 Preview delivers an early glimpse into the platform’s trajectory, with plans to roll out select text-based applications within Copilot over the coming weeks to gather user feedback and refine performance. Microsoft reinforces that it will continue combining its own models, partner models, and developments from the open-source community to flexibly power experiences across millions of unique interactions each day. -
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MAI-Voice-1
Microsoft
MAI-Voice-1 is Microsoft AI’s first highly expressive and natural speech generation model, designed to produce high-fidelity, emotionally rich audio across single- and multi-speaker scenarios with extraordinary efficiency, capable of generating a full minute of audio in under one second on a single GPU. Integrated into Copilot Daily and Podcasts, it powers a new Copilot Labs experience where users can test its expressive speech and storytelling capabilities, such as crafting “choose your own adventure” narratives or bespoke guided meditations using simple prompts. Voice is envisioned as the interface of the future for AI companions, and MAI-Voice-1 delivers this vision through its lightning-fast performance and realism, making it one of the most efficient speech systems available. Microsoft is exploring the potential of voice interfaces to create immersive, personalized AI interactions. -
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Incredible
Incredible
Incredible is a no-code automation platform powered by agentic AI models designed for real work across applications, letting users create AI “coworkers” that perform complex, multi-step workflows merely by describing tasks in plain English. These AI agents integrate with hundreds of productivity tools, CRMs, ERPs, email systems, Notion, HubSpot, OneDrive, Trello, Slack, and more to perform actions like content repurposing, CRM health checks, contract reviews, and content calendar updates without writing any code. Its architecture supports parallel execution of hundreds of actions with low latency and handles large datasets efficiently, dramatically reducing token limitations and hallucinations in data-critical tasks. The latest model, Incredible Small 1.0, is available in research preview and via API as a drop-in alternative to other LLM endpoints, offering high-precision data processing, near-zero hallucination, and enterprise-scale automation.
