Alternatives to Command A Vision

Compare Command A Vision alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Command A Vision in 2026. Compare features, ratings, user reviews, pricing, and more from Command A Vision competitors and alternatives in order to make an informed decision for your business.

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    Google Cloud Vision AI
    Derive insights from your images in the cloud or at the edge with AutoML Vision or use pre-trained Vision API models to detect emotion, understand text, and more. Google Cloud offers two computer vision products that use machine learning to help you understand your images with industry-leading prediction accuracy. Automate the training of your own custom machine learning models. Simply upload images and train custom image models with AutoML Vision’s easy-to-use graphical interface; optimize your models for accuracy, latency, and size; and export them to your application in the cloud, or to an array of devices at the edge. Google Cloud’s Vision API offers powerful pre-trained machine learning models through REST and RPC APIs. Assign labels to images and quickly classify them into millions of predefined categories. Detect objects and faces, read printed and handwritten text, and build valuable metadata into your image catalog.
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    Ray2

    Ray2

    Luma AI

    Ray2 is a large-scale video generative model capable of creating realistic visuals with natural, coherent motion. It has a strong understanding of text instructions and can take images and video as input. Ray2 exhibits advanced capabilities as a result of being trained on Luma’s new multi-modal architecture scaled to 10x compute of Ray1. Ray2 marks the beginning of a new generation of video models capable of producing fast coherent motion, ultra-realistic details, and logical event sequences. This increases the success rate of usable generations and makes videos generated by Ray2 substantially more production-ready. Text-to-video generation is available in Ray2 now, with image-to-video, video-to-video, and editing capabilities coming soon. Ray2 brings a whole new level of motion fidelity. Smooth, cinematic, and jaw-dropping, transform your vision into reality. Tell your story with stunning, cinematic visuals. Ray2 lets you craft breathtaking scenes with precise camera movements.
    Starting Price: $9.99 per month
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    Cohere

    Cohere

    Cohere AI

    Cohere is an enterprise AI platform that enables developers and businesses to build powerful language-based applications. Specializing in large language models (LLMs), Cohere provides solutions for text generation, summarization, and semantic search. Their model offerings include the Command family for high-performance language tasks and Aya Expanse for multilingual applications across 23 languages. Focused on security and customization, Cohere allows flexible deployment across major cloud providers, private cloud environments, or on-premises setups to meet diverse enterprise needs. The company collaborates with industry leaders like Oracle and Salesforce to integrate generative AI into business applications, improving automation and customer engagement. Additionally, Cohere For AI, their research lab, advances machine learning through open-source projects and a global research community.
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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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    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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    FLUX.1 Kontext

    FLUX.1 Kontext

    Black Forest Labs

    FLUX.1 Kontext is a suite of generative flow matching models developed by Black Forest Labs, enabling users to generate and edit images using both text and image prompts. This multimodal approach allows for in-context image generation, facilitating seamless extraction and modification of visual concepts to produce coherent renderings. Unlike traditional text-to-image models, FLUX.1 Kontext unifies instant text-based image editing with text-to-image generation, offering capabilities such as character consistency, context understanding, and local editing. Users can perform targeted modifications on specific elements within an image without affecting the rest, preserve unique styles from reference images, and iteratively refine creations with minimal latency.
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    HunyuanOCR

    HunyuanOCR

    Tencent

    Tencent Hunyuan is a large-scale, multimodal AI model family developed by Tencent that spans text, image, video, and 3D modalities, designed for general-purpose AI tasks like content generation, visual reasoning, and business automation. Its model lineup includes variants optimized for natural language understanding, multimodal vision-language comprehension (e.g., image & video understanding), text-to-image creation, video generation, and 3D content generation. Hunyuan models leverage a mixture-of-experts architecture and other innovations (like hybrid “mamba-transformer” designs) to deliver strong performance on reasoning, long-context understanding, cross-modal tasks, and efficient inference. For example, the vision-language model Hunyuan-Vision-1.5 supports “thinking-on-image”, enabling deep multimodal understanding and reasoning on images, video frames, diagrams, or spatial data.
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    Hunyuan-Vision-1.5
    HunyuanVision is a cutting-edge vision-language model developed by Tencent’s Hunyuan team. It uses a mamba-transformer hybrid architecture to deliver strong performance and efficient inference in multimodal reasoning tasks. The version Hunyuan-Vision-1.5 is designed for “thinking on images,” meaning it not only understands vision+language content, but can perform deeper reasoning that involves manipulating or reflecting on image inputs, such as cropping, zooming, pointing, box drawing, or drawing on the image to acquire additional knowledge. It supports a variety of vision tasks (image + video recognition, OCR, diagram understanding), visual reasoning, and even 3D spatial comprehension, all in a unified multilingual framework. The model is built to work seamlessly across languages and tasks and is intended to be open sourced (including checkpoints, technical report, inference support) to encourage the community to experiment and adopt.
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    Command R+

    Command R+

    Cohere AI

    Command R+ is Cohere's newest large language model, optimized for conversational interaction and long-context tasks. It aims at being extremely performant, enabling companies to move beyond proof of concept and into production. We recommend using Command R+ for those workflows that lean on complex RAG functionality and multi-step tool use (agents). Command R, on the other hand, is great for simpler retrieval augmented generation (RAG) and single-step tool use tasks, as well as applications where price is a major consideration.
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    Amazon Nova 2 Omni
    Nova 2 Omni is a fully unified multimodal reasoning and generation model capable of understanding and producing content across text, images, video, and speech. It can take in extremely large inputs, ranging from hundreds of thousands of words to hours of audio and lengthy videos, while maintaining coherent analysis across formats. This allows it to digest full product catalogs, long-form documents, customer testimonials, and complete video libraries all at the same time, giving teams a single system that replaces the need for multiple specialized models. With its ability to handle mixed media in one workflow, Nova 2 Omni opens new possibilities for creative and operational automation. A marketing team, for example, can feed in product specs, brand guidelines, reference images, and video content and instantly generate an entire campaign, including messaging, social content, and visuals, in one pass.
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    GPT-4V (Vision)
    GPT-4 with vision (GPT-4V) enables users to instruct GPT-4 to analyze image inputs provided by the user, and is the latest capability we are making broadly available. Incorporating additional modalities (such as image inputs) into large language models (LLMs) is viewed by some as a key frontier in artificial intelligence research and development. Multimodal LLMs offer the possibility of expanding the impact of language-only systems with novel interfaces and capabilities, enabling them to solve new tasks and provide novel experiences for their users. In this system card, we analyze the safety properties of GPT-4V. Our work on safety for GPT-4V builds on the work done for GPT-4 and here we dive deeper into the evaluations, preparation, and mitigation work done specifically for image inputs.
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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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    Command A

    Command A

    Cohere AI

    Command A, introduced by Cohere, is a high-performance AI model designed to maximize efficiency with minimal computational resources. This model outperforms or matches other top-tier models like GPT-4 and DeepSeek-V3 in agentic enterprise tasks while significantly reducing compute costs. It is tailored for applications requiring fast, efficient AI-driven solutions, providing businesses with the capability to perform advanced tasks across various domains, all while optimizing performance and computational demands.
    Starting Price: $2.50 / 1M tokens
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    Qwen2-VL

    Qwen2-VL

    Alibaba

    Qwen2-VL is the latest version of the vision language models based on Qwen2 in the Qwen model familities. Compared with Qwen-VL, Qwen2-VL has the capabilities of: SoTA understanding of images of various resolution & ratio: Qwen2-VL achieves state-of-the-art performance on visual understanding benchmarks, including MathVista, DocVQA, RealWorldQA, MTVQA, etc. Understanding videos of 20 min+: Qwen2-VL can understand videos over 20 minutes for high-quality video-based question answering, dialog, content creation, etc. Agent that can operate your mobiles, robots, etc.: with the abilities of complex reasoning and decision making, Qwen2-VL can be integrated with devices like mobile phones, robots, etc., for automatic operation based on visual environment and text instructions. Multilingual Support: to serve global users, besides English and Chinese, Qwen2-VL now supports the understanding of texts in different languages inside images
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    Hailuo 2.3

    Hailuo 2.3

    Hailuo AI

    Hailuo 2.3 is a next-generation AI video generator model available through the Hailuo AI platform that lets users create short videos from text prompts or static images with smooth motion, natural expressions, and cinematic polish. It supports multi-modal workflows where you describe a scene in plain language or upload a reference image and then generate vivid, fluid video content in seconds, handling complex motion such as dynamic dance choreography and lifelike facial micro-expressions with improved visual consistency over earlier models. Hailuo 2.3 enhances stylistic stability for anime and artistic video styles, delivers heightened realism in movement and expression, and maintains coherent lighting and motion throughout each generated clip. It offers a Fast mode variant optimized for speed and lower cost while still producing high-quality results, and it is tuned to address common challenges in ecommerce and marketing content.
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    Qwen3-VL

    Qwen3-VL

    Alibaba

    Qwen3-VL is the newest vision-language model in the Qwen family (by Alibaba Cloud), designed to fuse powerful text understanding/generation with advanced visual and video comprehension into one unified multimodal model. It accepts inputs in mixed modalities, text, images, and video, and handles long, interleaved contexts natively (up to 256 K tokens, with extensibility beyond). Qwen3-VL delivers major advances in spatial reasoning, visual perception, and multimodal reasoning; the model architecture incorporates several innovations such as Interleaved-MRoPE (for robust spatio-temporal positional encoding), DeepStack (to leverage multi-level features from its Vision Transformer backbone for refined image-text alignment), and text–timestamp alignment (for precise reasoning over video content and temporal events). These upgrades enable Qwen3-VL to interpret complex scenes, follow dynamic video sequences, read and reason about visual layouts.
  • 17
    GLM-4.5V-Flash
    GLM-4.5V-Flash is an open source vision-language model, designed to bring strong multimodal capabilities into a lightweight, deployable package. It supports image, video, document, and GUI inputs, enabling tasks such as scene understanding, chart and document parsing, screen reading, and multi-image analysis. Compared to larger models in the series, GLM-4.5V-Flash offers a compact footprint while retaining core VLM capabilities like visual reasoning, video understanding, GUI task handling, and complex document parsing. It can serve in “GUI agent” workflows, meaning it can interpret screenshots or desktop captures, recognize icons or UI elements, and assist with automated desktop or web-based tasks. Although it forgoes some of the largest-model performance gains, GLM-4.5V-Flash remains versatile for real-world multimodal tasks where efficiency, lower resource usage, and broad modality support are prioritized.
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    PaliGemma 2
    PaliGemma 2, the next evolution in tunable vision-language models, builds upon the performant Gemma 2 models, adding the power of vision and making it easier than ever to fine-tune for exceptional performance. With PaliGemma 2, these models can see, understand, and interact with visual input, opening up a world of new possibilities. It offers scalable performance with multiple model sizes (3B, 10B, 28B parameters) and resolutions (224px, 448px, 896px). PaliGemma 2 generates detailed, contextually relevant captions for images, going beyond simple object identification to describe actions, emotions, and the overall narrative of the scene. Our research demonstrates leading performance in chemical formula recognition, music score recognition, spatial reasoning, and chest X-ray report generation, as detailed in the technical report. Upgrading to PaliGemma 2 is a breeze for existing PaliGemma users.
  • 19
    Qwen-Image

    Qwen-Image

    Alibaba

    Qwen-Image is a multimodal diffusion transformer (MMDiT) foundation model offering state-of-the-art image generation, text rendering, editing, and understanding. It excels at complex text integration, seamlessly embedding alphabetic and logographic scripts into visuals with typographic fidelity, and supports diverse artistic styles from photorealism to impressionism, anime, and minimalist design. Beyond creation, it enables advanced image editing operations such as style transfer, object insertion or removal, detail enhancement, in-image text editing, and human pose manipulation through intuitive prompts. Its built-in vision understanding tasks, including object detection, semantic segmentation, depth and edge estimation, novel view synthesis, and super-resolution, extend its capabilities into intelligent visual comprehension. Qwen-Image is accessible via popular libraries like Hugging Face Diffusers and integrates prompt-enhancement tools for multilingual support.
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    Imagen 3

    Imagen 3

    Google

    Imagen 3 is the next evolution of Google's cutting-edge text-to-image AI generation technology. Building on the strengths of its predecessors, Imagen 3 offers significant advancements in image fidelity, resolution, and semantic alignment with user prompts. By employing enhanced diffusion models and more sophisticated natural language understanding, it can produce hyper-realistic, high-resolution images with intricate textures, vivid colors, and precise object interactions. Imagen 3 also introduces better handling of complex prompts, including abstract concepts and multi-object scenes, while reducing artifacts and improving coherence. With its powerful capabilities, Imagen 3 is poised to revolutionize creative industries, from advertising and design to gaming and entertainment, by providing artists, developers, and creators with an intuitive tool for visual storytelling and ideation.
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    Qwen2.5-VL

    Qwen2.5-VL

    Alibaba

    Qwen2.5-VL is the latest vision-language model from the Qwen series, representing a significant advancement over its predecessor, Qwen2-VL. This model excels in visual understanding, capable of recognizing a wide array of objects, including text, charts, icons, graphics, and layouts within images. It functions as a visual agent, capable of reasoning and dynamically directing tools, enabling applications such as computer and phone usage. Qwen2.5-VL can comprehend videos exceeding one hour in length and can pinpoint relevant segments within them. Additionally, it accurately localizes objects in images by generating bounding boxes or points and provides stable JSON outputs for coordinates and attributes. The model also supports structured outputs for data like scanned invoices, forms, and tables, benefiting sectors such as finance and commerce. Available in base and instruct versions across 3B, 7B, and 72B sizes, Qwen2.5-VL is accessible through platforms like Hugging Face and ModelScope.
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    LLaVA

    LLaVA

    LLaVA

    LLaVA (Large Language-and-Vision Assistant) is an innovative multimodal model that integrates a vision encoder with the Vicuna language model to facilitate comprehensive visual and language understanding. Through end-to-end training, LLaVA exhibits impressive chat capabilities, emulating the multimodal functionalities of models like GPT-4. Notably, LLaVA-1.5 has achieved state-of-the-art performance across 11 benchmarks, utilizing publicly available data and completing training in approximately one day on a single 8-A100 node, surpassing methods that rely on billion-scale datasets. The development of LLaVA involved the creation of a multimodal instruction-following dataset, generated using language-only GPT-4. This dataset comprises 158,000 unique language-image instruction-following samples, including conversations, detailed descriptions, and complex reasoning tasks. This data has been instrumental in training LLaVA to perform a wide array of visual and language tasks effectively.
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    Gemini Robotics

    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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    Kling 2.5

    Kling 2.5

    Kuaishou Technology

    Kling 2.5 is an AI video generation model designed to create high-quality visuals from text or image inputs. It focuses on producing detailed, cinematic video output with smooth motion and strong visual coherence. Kling 2.5 generates silent visuals, allowing creators to add voiceovers, sound effects, and music separately for full creative control. The model supports both text-to-video and image-to-video workflows for flexible content creation. Kling 2.5 excels at scene composition, camera movement, and visual storytelling. It enables creators to bring ideas to life quickly without complex editing tools. Kling 2.5 serves as a powerful foundation for visually rich AI-generated video content.
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    Synetic

    Synetic

    Synetic

    Synetic AI is a platform that accelerates the creation and deployment of real-world computer vision models by automatically generating photorealistic synthetic training datasets with pixel-perfect annotations and no manual labeling required, using advanced physics-based rendering and simulation to eliminate the traditional gap between synthetic and real-world data and achieve superior model performance. Its synthetic data has been independently validated to outperform real-world datasets by an average of 34% in generalization and recall, covering unlimited variations like lighting, weather, camera angles, and edge cases with comprehensive metadata, annotations, and multi-modal sensor support, enabling teams to iterate instantly and train models faster and cheaper than traditional approaches; Synetic AI supports common architectures and export formats, handles edge deployment and monitoring, and can deliver full datasets in about a week and custom trained models in a few weeks.
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    Ultralytics

    Ultralytics

    Ultralytics

    Ultralytics offers a full-stack vision-AI platform built around its flagship YOLO model suite that enables teams to train, validate, and deploy computer-vision models with minimal friction. The platform allows you to drag and drop datasets, select from pre-built templates or fine-tune custom models, then export to a wide variety of formats for cloud, edge or mobile deployment. With support for tasks including object detection, instance segmentation, image classification, pose estimation and oriented bounding-box detection, Ultralytics’ models deliver high accuracy and efficiency and are optimized for both embedded devices and large-scale inference. The product also includes Ultralytics HUB, a web-based tool where users can upload their images/videos, train models online, preview results (even on a phone), collaborate with team members, and deploy via an inference API.
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    Imagen 2

    Imagen 2

    Google

    Imagen 2 is a state-of-the-art AI-powered text-to-image generation model developed by Google Research. It leverages advanced diffusion models and large-scale language understanding to produce highly detailed, photorealistic images from natural language prompts. Imagen 2 builds on its predecessor, Imagen, with improved resolution, finer texture details, and enhanced semantic coherence, allowing for more accurate visual representations of complex and abstract concepts. Its unique blend of vision and language models enables it to handle a wide range of artistic, conceptual, and realistic image styles. This breakthrough technology has broad applications in fields like content creation, design, and entertainment, pushing the boundaries of creative AI.
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    Seedream 4.5

    Seedream 4.5

    ByteDance

    Seedream 4.5 is ByteDance’s latest AI-powered image-creation model that merges text-to-image synthesis and image editing into a single, unified architecture, producing high-fidelity visuals with remarkable consistency, detail, and flexibility. It significantly upgrades prior versions by more accurately identifying the main subject during multi-image editing, strictly preserving reference-image details (such as facial features, lighting, color tone, and proportions), and greatly enhancing its ability to render typography and dense or small text legibly. It handles both creation from prompts and editing of existing images: you can supply a reference image (or multiple), describe changes in natural language, such as “only keep the character in the green outline and delete other elements,” alter materials, change lighting or background, adjust layout and typography, and receive a polished result that retains visual coherence and realism.
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    Claude Pro

    Claude Pro

    Anthropic

    Claude Pro is an advanced large language model designed to handle complex tasks while maintaining a friendly, accessible demeanor. Trained on extensive, high-quality data, it excels at understanding context, interpreting subtle nuances, and producing well-structured, coherent responses across a wide range of topics. By leveraging robust reasoning capabilities and a refined knowledge base, Claude Pro can draft detailed reports, compose creative content, summarize lengthy documents, and even assist in coding tasks. Its adaptive algorithms continuously improve its ability to learn from feedback, ensuring that its output remains accurate, reliable, and helpful. Whether serving professionals seeking expert support or individuals looking for quick, informative answers, Claude Pro delivers a versatile and productive conversational experience.
  • 30
    Amazon Lookout for Vision
    Easily create a machine learning (ML) model to spot anomalies from your live process line with as few as 30 images. Identify visual anomalies in real time to reduce and prevent defects and improve product quality. Prevent unplanned downtime and reduce operational costs by using visual inspection data to spot potential issues and take corrective action. Spot damage to a product’s surface quality, color, and shape during the fabrication and assembly process. Determine what’s missing based on the absence, presence, or placement of objects, like a missing capacitor in a printed circuit board. Detect defects with repeating patterns, such as repeated scratches in the same spot on a silicon wafer. Amazon Lookout for Vision is an ML service that uses computer vision to spot defects in manufactured products at scale. Spot product defects using computer vision to automate quality inspection.
  • 31
    Cohere PaaS Intelligent Prior Authorization
    Cohere helps health plans digitize the process and apply clinical intelligence to enable in-house, end-to-end automation of prior authorization. Health plans can directly license Cohere’s PaaS intelligent prior authorization for use by the plan’s internal utilization management staff. As a result, our client health plans achieve both significant administrative efficiencies and faster, better patient outcomes. Cohere delivers a tailored, modular, and configurable solution suite for health plans. Digitizes all prior authorization requests into a single automated workflow. Automates prior authorization decisions using health plan-preferred policies and accelerates manual review. Helps clinical reviewers adjudicate complex requests, using responsible AI/ML and automated capabilities. Leverages clinical intelligence with AI/ML and advanced analytics to improve utilization management performance. Improves patient and population outcomes with innovative, specialty-specific programs.
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    GLM-4.1V

    GLM-4.1V

    Zhipu AI

    GLM-4.1V is a vision-language model, providing a powerful, compact multimodal model designed for reasoning and perception across images, text, and documents. The 9-billion-parameter variant (GLM-4.1V-9B-Thinking) is built on the GLM-4-9B foundation and enhanced through a specialized training paradigm using Reinforcement Learning with Curriculum Sampling (RLCS). It supports a 64k-token context window and accepts high-resolution inputs (up to 4K images, any aspect ratio), enabling it to handle complex tasks such as optical character recognition, image captioning, chart and document parsing, video and scene understanding, GUI-agent workflows (e.g., interpreting screenshots, recognizing UI elements), and general vision-language reasoning. In benchmark evaluations at the 10 B-parameter scale, GLM-4.1V-9B-Thinking achieved top performance on 23 of 28 tasks.
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    GLM-4.6V

    GLM-4.6V

    Zhipu AI

    GLM-4.6V is a state-of-the-art open source multimodal vision-language model from the Z.ai (GLM-V) family designed for reasoning, perception, and action. It ships in two variants: a full-scale version (106B parameters) for cloud or high-performance clusters, and a lightweight “Flash” variant (9B) optimized for local deployment or low-latency use. GLM-4.6V supports a native context window of up to 128K tokens during training, enabling it to process very long documents or multimodal inputs. Crucially, it integrates native Function Calling, meaning the model can take images, screenshots, documents, or other visual media as input directly (without manual text conversion), reason about them, and trigger tool calls, bridging “visual perception” with “executable action.” This enables a wide spectrum of capabilities; interleaved image-and-text content generation (for example, combining document understanding with text summarization or generation of image-annotated responses).
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    FLUX.2 [max]

    FLUX.2 [max]

    Black Forest Labs

    FLUX.2 [max] is the flagship image-generation and editing model in the FLUX.2 family from Black Forest Labs that delivers top-tier photorealistic output with professional-grade quality and unmatched consistency across styles, objects, characters, and scenes. It supports grounded generation that can incorporate real-time contextual information, enabling visuals that reflect current trends, environments, and detailed prompt intent while maintaining coherence and structure. It excels at producing marketplace-ready product photos, cinematic visuals, logo and brand assets, and high-fidelity creative imagery with precise control over colors, lighting, composition, and textures, and it preserves identity even through complex edits and multi-reference inputs. FLUX.2 [max] handles detailed features such as character proportions, facial expressions, typography, and spatial reasoning with high stability, making it suitable for iterative creative workflows.
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    WowYow

    WowYow

    WowYow AI

    WowYow’s patented technology processes visual content 8x faster and is up to 10x more cost-effective than major computer vision providers. Affordable and Accessible AI, wow, that's powerful. Computer Vision and Metadata help us understand visual content, but we don't stop there. Combine them with unique business logic to address your business needs. Since the beginning, WowYow has focused on engineering products that advance industries forward. From contextual advertising to streaming metadata we build products and deliver solutions unlike any other.
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    Coherent

    Coherent

    Synergy Information Systems

    Maximize operational efficiency with Coherent, the premier facilities maintenance management software. Coherent helps companies work smarter everyday by offering a plethora of tools for optimizing their maintenance resources, improving equipment and staff, and enabling better decision making. Easy to use and intuitive, Coherent top features include work order management, preventive maintenance, asset tracking, vendor management, dashboard and calendars, and more.
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    North

    North

    Cohere AI

    North is an integrated AI platform developed by Cohere that combines large language models, intelligent search, and automation into a secure, scalable workspace. Designed to enhance workforce productivity and operational efficiency, North enables teams to focus on meaningful work by providing personalized AI agents and advanced search capabilities. The platform seamlessly integrates with existing workflows, offering a user-friendly interface that empowers modern workers to accomplish more within a secure environment. By leveraging North's capabilities, enterprises can automate repetitive tasks, surface business insights, and deploy AI solutions that are both powerful and adaptable, all while maintaining robust security and data protection standards. To explore how North can transform your organization's productivity and efficiency, you can join the waitlist or request a demo through Cohere's official website.
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    BLOOM

    BLOOM

    BigScience

    BLOOM is an autoregressive Large Language Model (LLM), trained to continue text from a prompt on vast amounts of text data using industrial-scale computational resources. As such, it is able to output coherent text in 46 languages and 13 programming languages that is hardly distinguishable from text written by humans. BLOOM can also be instructed to perform text tasks it hasn't been explicitly trained for, by casting them as text generation tasks.
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    Selene 1
    Atla's Selene 1 API offers state-of-the-art AI evaluation models, enabling developers to define custom evaluation criteria and obtain precise judgments on their AI applications' performance. Selene outperforms frontier models on commonly used evaluation benchmarks, ensuring accurate and reliable assessments. Users can customize evaluations to their specific use cases through the Alignment Platform, allowing for fine-grained analysis and tailored scoring formats. The API provides actionable critiques alongside accurate evaluation scores, facilitating seamless integration into existing workflows. Pre-built metrics, such as relevance, correctness, helpfulness, faithfulness, logical coherence, and conciseness, are available to address common evaluation scenarios, including detecting hallucinations in retrieval-augmented generation applications or comparing outputs to ground truth data.
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    Passio

    Passio

    Passio

    Our easy-to-use SDKs reach millions of users who use Passio every day to transform their health, homes, businesses and lives. We help businesses transform their applications with real-time, on-device computer vision and AI-driven user experiences. Bring your paint and home improvement store into the homes of your customers and allow them to visualize and purchase your paint and home remodel products. Help your customers make better buying decision by seeing your products in their homes in augmented reality and by using computer vision to identify their remodel scenarios, surface types and surface conditions. Remodel AI comes with a flexible painter which takes advantage of the latest AR technology and offers you multiple methods for room scanning and paint visualization. It takes seconds tor transform the room and your users will be delighted to see their new environments in real-time on their iOS and Android devices.
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    Qwen2.5

    Qwen2.5

    Alibaba

    Qwen2.5 is an advanced multimodal AI model designed to provide highly accurate and context-aware responses across a wide range of applications. It builds on the capabilities of its predecessors, integrating cutting-edge natural language understanding with enhanced reasoning, creativity, and multimodal processing. Qwen2.5 can seamlessly analyze and generate text, interpret images, and interact with complex data to deliver precise solutions in real time. Optimized for adaptability, it excels in personalized assistance, data analysis, creative content generation, and academic research, making it a versatile tool for professionals and everyday users alike. Its user-centric design emphasizes transparency, efficiency, and alignment with ethical AI practices.
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    Cohere Embed
    Cohere's Embed is a leading multimodal embedding platform designed to transform text, images, or a combination of both into high-quality vector representations. These embeddings are optimized for semantic search, retrieval-augmented generation, classification, clustering, and agentic AI applications.​ The latest model, embed-v4.0, supports mixed-modality inputs, allowing users to combine text and images into a single embedding. It offers Matryoshka embeddings with configurable dimensions of 256, 512, 1024, or 1536, enabling flexibility in balancing performance and resource usage. With a context length of up to 128,000 tokens, embed-v4.0 is well-suited for processing large documents and complex data structures. It also supports compressed embedding types, including float, int8, uint8, binary, and ubinary, facilitating efficient storage and faster retrieval in vector databases. Multilingual support spans over 100 languages, making it a versatile tool for global applications.
    Starting Price: $0.47 per image
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    Grok 4.1 Thinking
    Grok 4.1 Thinking is xAI’s advanced reasoning-focused AI model designed for deeper analysis, reflection, and structured problem-solving. It uses explicit thinking tokens to reason through complex prompts before delivering a response, resulting in more accurate and context-aware outputs. The model excels in tasks that require multi-step logic, nuanced understanding, and thoughtful explanations. Grok 4.1 Thinking demonstrates a strong, coherent personality while maintaining analytical rigor and reliability. It has achieved the top overall ranking on the LMArena Text Leaderboard, reflecting strong human preference in blind evaluations. The model also shows leading performance in emotional intelligence and creative reasoning benchmarks. Grok 4.1 Thinking is built for users who value clarity, depth, and defensible reasoning in AI interactions.
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    Pixtral Large

    Pixtral Large

    Mistral AI

    Pixtral Large is a 124-billion-parameter open-weight multimodal model developed by Mistral AI, building upon their Mistral Large 2 architecture. It integrates a 123-billion-parameter multimodal decoder with a 1-billion-parameter vision encoder, enabling advanced understanding of documents, charts, and natural images while maintaining leading text comprehension capabilities. With a context window of 128,000 tokens, Pixtral Large can process at least 30 high-resolution images simultaneously. The model has demonstrated state-of-the-art performance on benchmarks such as MathVista, DocVQA, and VQAv2, surpassing models like GPT-4o and Gemini-1.5 Pro. Pixtral Large is available under the Mistral Research License for research and educational use, and under the Mistral Commercial License for commercial applications.
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    HunyuanWorld
    HunyuanWorld-1.0 is an open source AI framework and generative model developed by Tencent Hunyuan that creates immersive, explorable, and interactive 3D worlds from text prompts or image inputs by combining the strengths of 2D and 3D generation techniques into a unified pipeline. At its core, the project features a semantically layered 3D mesh representation that uses 360° panoramic world proxies to decompose and reconstruct scenes with geometric consistency and semantic awareness, enabling the creation of diverse, coherent environments that can be navigated and interacted with. Unlike traditional 3D generation methods that struggle with either limited diversity or inefficient data representations, HunyuanWorld-1.0 integrates panoramic proxy generation, hierarchical 3D reconstruction, and semantic layering to balance high visual quality and structural integrity while enabling exportable meshes compatible with common graphics workflows.
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    LTM-1

    LTM-1

    Magic AI

    Magic’s LTM-1 enables 50x larger context windows than transformers. Magic's trained a Large Language Model (LLM) that’s able to take in the gigantic amounts of context when generating suggestions. For our coding assistant, this means Magic can now see your entire repository of code. Larger context windows can allow AI models to reference more explicit, factual information and their own action history. We hope to be able to utilize this research to improve reliability and coherence.
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    Kimi K2.5

    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.
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    MagicLight

    MagicLight

    MagicLight

    MagicLight AI is an AI-powered story-video generator that transforms user-submitted scripts or story concepts into fully animated, coherent videos, complete with consistent characters, visual style, scene transitions, and narration, without requiring any technical video-editing skills. Users simply input their idea or narrative concept, and the tool uses proprietary models to generate a storyboard, create full scenes with character continuity and style uniformity, and synthesize long-form animations (up to around 30 minutes) in one workflow. It supports multiple genres, children’s stories, history, science education, religious/spiritual content, social media clips, and allows creators to customize characters, backgrounds, animation style, and voiceover. MagicLight prioritizes long-form narrative coherence and combines image-to-video modelling with story-understanding logic so that plot, characters, and emotions remain consistent.
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    GPT-5.2 Thinking
    GPT-5.2 Thinking is the highest-capability configuration in OpenAI’s GPT-5.2 model family, engineered for deep, expert-level reasoning, complex task execution, and advanced problem solving across long contexts and professional domains. Built on the foundational GPT-5.2 architecture with improvements in grounding, stability, and reasoning quality, this variant applies more compute and reasoning effort to generate responses that are more accurate, structured, and contextually rich when handling highly intricate workflows, multi-step analysis, and domain-specific challenges. GPT-5.2 Thinking excels at tasks that require sustained logical coherence, such as detailed research synthesis, advanced coding and debugging, complex data interpretation, strategic planning, and sophisticated technical writing, and it outperforms lighter variants on benchmarks that test professional skills and deep comprehension.
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    Eyeris

    Eyeris

    Eyeris

    Driven by excellence, inspired by you. At Eyeris, our technology was inspired by the late-night worker, the caring parent, the aspiring entrepreneur. Keeping every driver in mind, our innovative technology promises to push towards a safer and better road ahead. ​In-Cabin cameras are the most common sensor used for driver and occupant monitoring. Eyeris AI Software interprets the entire interior scene through these cameras. Allows the ability to collect data from different sensor types to interpret the scene with redundant data for high data accuracy. Innovation in hardware is improving to accommodate and run sophisicated AI software in the most efficient and fastest manner. Our vision-based neural networks provide the richest source of information. Using the latest image sensors, our pre-trained vision AI models understand the entire in-cabin space under the widest range of lighting spectrum.