Compare the Top AI Models as of November 2026 - Page 17

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  • 1
    Seed2.0 Mini

    Seed2.0 Mini

    ByteDance

    Seed2.0 Mini is the smallest member of ByteDance’s Seed2.0 series of general-purpose multimodal agent models, designed for high-throughput inference and dense deployment while retaining the core strengths of its larger siblings in multimodal understanding and instruction following. Part of a family that also includes Pro and Lite, the Mini variant is optimized for high-concurrency and batch generation workloads, making it suitable for applications where efficient processing of many requests at scale matters as much as capability. Like other Seed2.0 models, it benefits from systematic enhancements in visual reasoning, motion perception, structured extraction from complex inputs like text and images, and reliable execution of multi-step instructions, but it trades some raw reasoning and output quality for faster, more cost-effective inference and better deployment efficiency.
  • 2
    SeedEdit 3.0

    SeedEdit 3.0

    ByteDance

    SeedEdit is a generative AI image editing model from ByteDance’s Seed team that enables text-guided, high-quality image modification by applying natural language instructions to change specific parts of an image while maintaining consistency in the rest of the scene. Built on advanced diffusion and multimodal learning techniques, later versions like SeedEdit 3.0 improve on earlier releases with enhanced fidelity, accurate instruction following, and the ability to edit at high resolution (including up to 4K outputs) while preserving original subjects, backgrounds, and fine visual details. It supports common edit tasks such as portrait retouching, background replacement, object removal, lighting and perspective changes, and stylistic transformations without manual masking or tools, and achieves higher usability and visual quality than previous models by balancing between reconstruction and regeneration of images.
  • 3
    Seedance 1.5 pro
    Seedance 1.5 Pro is a next-generation AI audio-video generation model developed by ByteDance’s Seed research team that produces native, synchronized video and sound in a single unified pass from text prompts and image or visual inputs, eliminating the traditional need to create visuals first and add audio later. It features joint audio-visual generation with highly accurate lip-sync and motion alignment, supporting multilingual audio and spatial sound effects that match the visuals for immersive storytelling and dialogue, and it maintains visual consistency and cinematic motion across multi-shot sequences including camera moves and narrative continuity. Able to generate short clips (typically 4–12 seconds) in up to 1080p quality with expressive motion, stable aesthetics, and optional first- and last-frame control, the model works for both text-to-video and image-to-video workflows so creators can animate static images or build full cinematic sequences with coherent narrative flow.
  • 4
    Seedream 4.0

    Seedream 4.0

    ByteDance

    Seedream 4.0 is a next-generation multimodal AI image generation and editing model that unifies text-to-image creation and text-guided image editing within a single architecture, delivering professional-grade visuals up to 4K resolution with exceptional fidelity and speed. It’s built around an efficient diffusion transformer and variational autoencoder design that lets it interpret text prompts and reference images to produce highly detailed, consistent outputs while handling complex semantics, lighting, and structure reliably, and it offers batch generation, multi-reference support, and precise control over edits such as style, background, or object changes without degrading the rest of the scene. Seedream 4.0 demonstrates industry-leading prompt understanding, aesthetic quality, and structural stability across generation and editing tasks, outperforming earlier versions and rival models in benchmarks for prompt adherence and visual coherence.
  • 5
    Seed1.8

    Seed1.8

    ByteDance

    Seed1.8 is ByteDance’s latest generalized agentic AI model designed to bridge understanding and real-world action by combining multimodal perception, agent-like task execution, and wide-ranging reasoning capabilities into a single foundation model that goes beyond simple language generation. It supports multimodal inputs, including text, images, and video, processes very large context windows (hundreds of thousands of tokens at once), and is optimized to handle complex workflows in real environments, such as information retrieval, code generation, GUI interaction, and multi-step decision logic, with efficient, accurate responses suitable for real-world applications. Seed1.8 unifies skills such as search, code understanding, visual context interpretation, and autonomous reasoning so developers and AI systems can build interactive agents and next-generation workflows capable of synthesizing evidence, following instructions deeply, and acting on tasks like automation.
  • 6
    Qwen3.5-Plus
    Qwen3.5-Plus is a high-performance native vision-language model designed for efficient text generation, deep reasoning, and multimodal understanding. Built on a hybrid architecture that combines linear attention with a sparse mixture-of-experts design, it delivers strong performance while optimizing inference efficiency. The model supports text, image, and video inputs and produces text outputs, making it suitable for complex multimodal workflows. With a massive 1 million token context window and up to 64K output tokens, Qwen3.5-Plus enables long-form reasoning and large-scale document analysis. It includes advanced capabilities such as structured outputs, function calling, web search, and tool integration via the Responses API. The model supports prefix continuation, caching, batch processing, and fine-tuning for flexible deployment. Designed for developers and enterprises, Qwen3.5-Plus provides scalable, high-throughput AI performance with OpenAI-compatible API access.
    Starting Price: $0.4 per 1M tokens
  • 7
    Higgsfield Soul 2.0
    Higgsfield Soul 2.0 is a foundation AI image generation model built for creative, fashion-aware, culture-native visual production. It is designed specifically for aesthetics, producing realistic images with “taste built into every image” and outputs that feel photographed rather than artificially generated. It enables users to generate visuals from either text prompts or reference images, with the model interpreting composition, lighting, styling cues, and mood to deliver editorial-quality results. Soul 2.0 includes curated presets that act as visual anchors, allowing creators to establish mood and style instantly without complex prompt engineering. A key component is Soul ID, a personalization layer that lets users train a consistent digital character from their own photos and reuse that identity across different scenes, poses, and lighting setups.
    Starting Price: $9 per month
  • 8
    Voxtral TTS

    Voxtral TTS

    Mistral AI

    Voxtral TTS is a state-of-the-art, multilingual text-to-speech model designed to generate highly realistic and emotionally expressive speech from text, combining strong contextual understanding with advanced speaker modeling to produce natural, human-like audio output. Built as a lightweight model with around 4 billion parameters, it delivers efficient performance while maintaining high quality, enabling scalable deployment for enterprise voice applications. It supports nine major languages and diverse dialects, and can adapt to new voices using only a short reference audio sample, capturing not just tone but also rhythm, pauses, intonation, and emotional nuance. Its zero-shot voice cloning capabilities allow it to replicate a speaker’s style without additional training, and it can even perform cross-lingual voice adaptation, generating speech in one language while preserving the accent of another.
  • 9
    Veo 3.1 Lite
    Veo 3.1 Lite is a cost-effective video generation model developed by Google DeepMind for developers building AI-powered applications. It enables users to create videos from text or images using advanced generative AI capabilities. The model supports multiple formats, including landscape and portrait orientations, as well as HD resolutions like 720p and 1080p. Designed for efficiency, it delivers high-speed performance at a lower cost compared to other models in the Veo family. Developers can customize video duration, allowing flexibility in content creation. Veo 3.1 Lite is accessible through the Gemini API and Google AI Studio. Overall, it makes scalable video generation more affordable and accessible for developers.
    Starting Price: $0.05 per second
  • 10
    Qwen3.5-Omni
    Qwen3.5-Omni is a next-generation, fully multimodal AI model developed by Alibaba that natively understands and generates text, images, audio, and video within a single unified system, enabling more natural and real-time human-AI interaction. Unlike traditional models that treat modalities separately, it is trained from the ground up on massive audiovisual datasets, allowing it to process complex inputs such as long audio streams, video, and spoken instructions simultaneously while maintaining strong performance across all formats. It supports long-context inputs of up to 256K tokens and can handle over 10 hours of audio or extended video sequences, making it suitable for demanding real-world applications. A key feature is its advanced voice interaction capabilities, including end-to-end speech dialogue, emotional tone control, and voice cloning, enabling highly natural conversational experiences that can whisper, shout, or adapt speaking style dynamically.
  • 11
    Wan2.7-Image
    Wan2.7-Image is a powerful AI-driven image generation model designed to create high-quality visuals from simple text inputs. It enables users to produce detailed and visually compelling images for a wide range of applications, including marketing, design, and digital content creation. The model supports various styles, allowing users to generate everything from realistic images to artistic and abstract visuals. Wan2.7-Image is optimized for both speed and quality, ensuring consistent and professional results across different use cases. It allows creators to quickly turn ideas into visual content without the need for advanced design skills. It can be integrated into existing workflows, making it a valuable tool for teams and individuals. It supports rapid experimentation, enabling users to iterate on concepts and refine outputs efficiently. Wan2.7-Image helps reduce production time and costs by automating the image creation process.
  • 12
    GLM-5V-Turbo
    GLM-5V-Turbo is a multimodal coding foundation model designed for vision-based coding tasks, capable of natively processing inputs such as images, video, text, and files while producing text outputs. It is optimized for agent workflows, enabling a full loop of understanding environments, planning actions, and executing tasks, and integrates seamlessly with agent frameworks like Claude Code and OpenClaw. It supports long-context interactions with a context length of 200K tokens and up to 128K output tokens, making it suitable for complex, long-horizon tasks. It offers multiple thinking modes for different scenarios, strong vision comprehension across images and video, real-time streaming output for improved interaction, and advanced function-calling capabilities for integrating external tools. It also includes context caching to enhance performance in extended conversations. In practical use, it can reconstruct frontend projects from design mockups.
  • 13
    SWE-1.6

    SWE-1.6

    Cognition

    SWE-1.6 is an engineering–focused AI model developed by Cognition and integrated into the Devin (Windsurf) environment, designed to optimize both raw intelligence and what the company calls “model UX,” or the overall feel and efficiency of interacting with an AI agent. It represents a new iteration in the SWE model family, improving performance on benchmarks such as SWE-Bench Pro by over 10% compared to SWE-1.5 while maintaining similar underlying capabilities. It was trained from scratch to jointly improve reasoning quality and user experience, addressing issues observed in earlier versions such as overthinking simple problems, taking too many steps, looping in repetitive reasoning, and relying excessively on terminal commands instead of specialized tools. SWE-1.6 introduces behavioral improvements such as more frequent parallel tool usage, faster context retrieval, and reduced need for user input, resulting in smoother and more efficient workflows.
  • 14
    Gemini Robotics-ER 1.6

    Gemini Robotics-ER 1.6

    Google DeepMind

    Gemini Robotics-ER 1.6 is a family of AI models developed by Google DeepMind to bring advanced multimodal intelligence into the physical world by enabling robots to perceive, reason, and act in real-world environments. Built on the Gemini 2.0 foundation, it extends traditional AI capabilities by adding physical action as an output modality, allowing robots to interpret visual input and natural language instructions and convert them directly into motor commands to complete tasks. It includes a vision-language-action model that processes images and instructions to execute tasks, as well as a complementary embodied reasoning model (Gemini Robotics-ER) that specializes in spatial understanding, planning, and decision-making within physical environments. These models enable robots to generalize across new situations, objects, and environments, allowing them to perform complex, multi-step tasks even if they were not explicitly trained for them.
  • 15
    GPT-Rosalind
    GPT-Rosalind is a purpose-built frontier reasoning model developed by OpenAI to accelerate scientific research across biology, drug discovery, and translational medicine. It is designed specifically for life sciences workflows, where researchers must navigate large volumes of literature, experimental data, and specialized databases to generate and validate new ideas. It combines deep domain understanding in areas such as chemistry, genomics, protein engineering, and disease biology with advanced tool-use capabilities, allowing it to interact with scientific databases, analyze experimental outputs, and support complex, multi-step reasoning tasks. It can assist with evidence synthesis, hypothesis generation, literature review, sequence interpretation, and experimental planning, helping scientists move faster from raw data to actionable insights. GPT-Rosalind transforms complex, time-intensive research processes into more efficient AI-assisted workflows.
  • 16
    GLM-Image
    GLM-Image is a next-generation, open source image generation model developed by Z.ai, designed to combine deep language understanding with high-fidelity visual synthesis. Unlike traditional diffusion-only models, it uses a hybrid architecture that integrates an autoregressive language model with a diffusion decoder, enabling it to first reason about the structure, meaning, and relationships within a prompt before generating the image itself. This approach allows GLM-Image to excel in scenarios that require precise semantic control, such as generating infographics, presentation slides, posters, and diagrams with accurate embedded text and complex layouts. With a total of around 16 billion parameters, the model achieves strong performance in rendering readable, correctly placed text within images, an area where many image models struggle, while maintaining detailed visual quality and consistency.
  • 17
    Qwen3.6

    Qwen3.6

    Alibaba

    Qwen3.6 is a large language model developed by Alibaba as part of its Qwen AI model family, designed for real-world applications and advanced reasoning tasks. It focuses on improving stability, usability, and performance compared to earlier versions. The model supports multimodal capabilities, allowing it to process and reason across text, images, and other data types. Qwen3.6 is particularly strong in coding and developer workflows, offering improved accuracy for complex programming tasks. It uses a mixture-of-experts architecture, enabling efficient performance while maintaining large-scale model capabilities. The model is designed to be deployable in production environments, including enterprise and cloud-based systems. It can be integrated into applications or run locally using open-weight variants. Overall, Qwen3.6 delivers a powerful, efficient, and versatile AI solution for modern use cases.
    Starting Price: Free
  • 18
    Odyssey-2 Max
    Odyssey-2 Max is a scaled, real-time world simulation model designed to move beyond traditional generative AI by learning how the physical world behaves and enabling continuous, interactive environments. It represents the third and most advanced model in the Odyssey-2 family, significantly increasing scale with three times the parameters and ten times the training compute compared to Odyssey-2 Pro, which unlocks new emergent behaviors and more stable, realistic simulations. It is built to simulate physics, human motion, interaction, and environmental dynamics in real time, generating continuous streams of visual output that respond instantly to user input instead of producing fixed clips. Unlike conventional video models that generate short, precomputed sequences, Odyssey-2 Max produces long-running simulations that evolve frame by frame, allowing users to interact with the environment as it unfolds.
  • 19
    Wan2.7 VideoEdit
    Wan2.7 VideoEdit, available in Alibaba Cloud Model Studio, is an instruction-based AI video editing model designed to transform existing video content through natural language commands while preserving the original structure and motion. Instead of generating videos from scratch, it allows users to upload a source clip and describe desired changes such as modifying backgrounds, adjusting lighting, altering colors, applying stylistic transformations, or even changing elements like clothing, enabling iterative refinement without restarting the creative process. As part of the broader Wan2.7 multimedia system, it integrates seamlessly with other capabilities, including text-to-video, image-to-video, and reference-based generation, forming a unified workflow that supports creation, editing, continuation, and reshaping of visual content. The model emphasizes high-quality output with improved motion smoothness, visual coherence, and support for HD formats.
    Starting Price: $0.1 per second
  • 20
    GPT-5.5 Instant
    GPT-5.5 Instant is ChatGPT’s updated default model, designed to be smarter and more accurate, with clearer, more concise answers that feel better tailored to each user. Built as a daily driver for hundreds of millions of people, this update makes everyday interactions more useful and enjoyable through stronger and tighter answers across subject areas, a more natural conversational tone, and better use of shared context when personalization can help. GPT-5.5 Instant is more dependable, with significant improvements in factuality, especially in domains where accuracy matters most, including medicine, law, and finance. It is more capable across everyday tasks, with improvements in analyzing photo and image uploads, answering STEM-related questions, and deciding when to use web search to provide a more useful answer. Responses are tighter and more to the point without losing substance, while keeping the warmth and personality that makes ChatGPT enjoyable to use.
  • 21
    Reactor

    Reactor

    Reactor

    Reactor is building the missing layer for world models and invites users to experience real-time world models through an early preview. Its product direction centers on worlds generated in real time, where pixels, sounds, and actions can be produced on the fly, changing how people interact with software and, eventually, the physical world. The preview is the first step toward that reality, letting users experience AI-generated worlds running on global low-latency infrastructure. Reactor’s work is focused on the next frontier of AI, real-time world models that people, agents, and robots can drive frame by frame. Rather than treating generated video as something passive to watch, Reactor points toward interactive environments that can be inhabited, controlled, and shaped as they generate. Its research and product focus includes real-time interactivity, inference, controllable world models, and systems that make dynamic visual environments responsive enough for live experiences.
    Starting Price: Free
  • 22
    Lumen Outpost
    Lumen Outpost is Cosine’s targeted post-trained coding model, benchmarked against Kimi K2.6, its base model, GPT-5.5, GPT-5.4, and Gemini 3.1 Pro on highly complex, long-horizon coding tasks across 13 programming languages. The model is specialized not only for raw coding accuracy, but also for behavioral signals that matter in professional engineering workflows, including agent initiative, planning, scope discipline, action alignment, concise updates, and useful communication. Cosine’s benchmark report shows that highly targeted post-training transformed the base model’s capabilities, with Lumen Outpost outperforming Kimi K2.6 across Niche-Bench, Slop-Bench, Vibe-Bench, and cost per successful task. On Niche-Bench, an internal evaluation for niche, legacy, and environment-constrained programming languages, Lumen Outpost achieved a 53.9% score and led or tied in 9 of 13 assessed languages, with notable gains in Fortran, ABAP, Java, and Rust.
    Starting Price: $20 per month
  • 23
    MiniMax Speech 2.8
    MiniMax Speech 2.8 is a next-generation AI speech model built to make synthetic voice feel alive, expressive, and deeply human. It focuses on performance in real-world voice agent scenarios, combining ultra-fast response, richer emotional expression, cleaner audio, and stronger cross-lingual performance for products that need natural spoken interaction. Speech 2.8 is designed to reduce the distance between AI voice and real human communication, giving developers and creators more control over how a voice sounds, reacts, and carries meaning. It supports flexible emotion control, allowing users to shape delivery with moods, tone, and expressive direction instead of relying on flat or robotic speech. It can produce speech with more natural pauses, cadence, emphasis, and emotional texture, helping AI characters, assistants, narrators, and interactive agents sound more believable across longer conversations.
  • 24
    MiniMax Music 2.6
    MiniMax Music 2.6 is an AI music generation model designed to help users create expressive, controlled, and production-ready music from natural language prompts. Instead of presenting the model only through technical specs, MiniMax describes Music 2.6 through real creative scenarios: a flamenco dancer building a solo track with dramatic pauses, an indie game developer scoring a boss fight with powerful low-end, a cafe owner creating a playlist with the right mood, and a daughter making a personalized cover version of a familiar song. It focuses on musical details that matter in real use, including tension, silence, rhythm, emotional build, low-frequency impact, imperfect vocals, melody feel, and genre transformation. Music 2.6 improves instruction control so users can include BPM, key, song structure, emotional arc, and specific creative direction directly in a prompt, with the model following those requirements more accurately.
  • 25
    CogVideoX-3
    CogVideoX-3 is a video generation model with new frame generation capabilities that significantly improve image stability and clarity. It delivers superior performance when handling subjects with significant movement, better adheres to instructions, and provides more realistic simulations. It supports image, text, and start-and-end-frame inputs, with video as the output modality, making it useful across text-to-video, image-to-video, and transition-based video workflows. CogVideoX-3 can be used for advertising and marketing by inputting product images or copy to quickly generate dynamic ads in multiple styles, supporting scene transitions and realistic lighting rendering. It also supports short video creation by converting single-frame images or text scripts into smooth, naturally animated short videos, covering both realistic and 3D styles. For tourism promotion, users can upload scenic spot photos and promotional text to generate immersive short videos.
    Starting Price: $0.2 per video
  • 26
    Ray3.2

    Ray3.2

    Luma AI

    Ray3.2 transforms creative intent into scalable video workflows with richer control, continuity, and cinematic direction. Built to help teams direct any frame and finish every cut, Ray3.2 brings direction, performance, transformation, motion, and finish into a single model at cinematic-grade quality. Multi-Keyframe lets users set up to 16 keyframes inside a single clip, directing what changes, what holds, and how the story lands, frame by frame. Modify Video V2 reshapes existing footage into new stories, allowing teams to swap the wall, the world, or the wardrobe while lighting holds and performance survives, with up to 20 seconds at 1080p. Reframe helps create once and deliver everywhere, handling every aspect ratio, while improved Motion Transfer keeps choreography and Expressive Facial Performance preserves the actor’s read. Ray3.2 can transfer movement and dynamics across characters, objects, and materials; transfer cinematic camera moves across scenes, worlds, and styles.
    Starting Price: $30 per month
  • 27
    Starchild-1
    Starchild-1 is the first real-time multimodal world model, built to simulate both the visuals and sounds of the world in real time. Unlike language models, which learn from text, world models learn directly from the world itself through pixels, motion, and actions encoded in large-scale video, becoming capable of understanding and simulating an approximation of the world as it evolves. Starchild-1 goes beyond traditional world models, which have mostly focused on visual generation alone, by autoregressively generating synchronized audio and video while continuously responding to streaming user input. Instead of producing a fixed offline clip, it predicts the next audio and video state of a world based on past observations and live inputs, enabling environments, conversations, ambient sound, and world dynamics to change interactively. Users can stream text, speech, and action inputs into the model during rollout, dynamically altering what is seen and heard in real time.
  • 28
    Agora-1

    Agora-1

    Odyssey

    Agora-1 is a multi-agent world model that enables multiple participants, human or AI, to share and interact within the same world simulation in real time. It is the first in a series of multi-agent world models exploring how world models can enable new shared experiences across gaming, robotics, defense, education, foundation models, and more. World models generate high-fidelity simulations of arbitrary environments, but until now, they have largely been limited to a single active participant inside those simulated worlds. Agora-1 introduces multi-agent world simulations by allowing up to four players to interact in the same generated world at once. Players are matched into a shared deathmatch simulation, where every participant interacts with the same world simultaneously while the model simulates player actions, maintains shared world state, and streams generated pixels to each player.
  • 29
    Mistral OCR 4

    Mistral OCR 4

    Mistral AI

    Mistral OCR 4 is a document extraction and understanding model built for enterprise search, RAG, domain-specific retrieval pipelines, and production-grade document intelligence. It extracts and structures content from a wide range of documents, moving beyond clean text and tables to return a structured representation of each page. Alongside extracted text, OCR 4 provides bounding boxes, typed-block classification, and inline confidence scores, helping downstream systems understand not only what the document says, but where each element sits, what role it plays, and how confident the model is in each region. Bounding boxes make in-context highlighting and reliable data pipelines possible, while block types and confidence scores support source-grounded citations, redactions, and human-in-the-loop verification. OCR 4 accepts common enterprise formats, including PDF, DOC, PPT, and OpenDocument, and supports 170 languages across 10 language groups.
    Starting Price: $2 per 1000 pages
  • 30
    Ling 2.6

    Ling 2.6

    Ant Group

    Ling 2.6 is a general-purpose large language model series independently developed and open-sourced by Ant Group, built on a Mixture of Experts architecture and designed for inference efficiency, long context modeling, training technology, and AI Agent collaborative reasoning. Ling’s MoE architecture routes each token to activate only the most relevant expert subnetworks, compressing actual computation to a minimal fraction while maintaining large-scale model capacity. The Ling 2.6 series further advances long-sequence modeling, with Ling-2.6-1T supporting up to a 1M native context window and the official API exposing a 256K context window, while Ling-2.6-flash provides a native 256K context window capable of processing approximately 200,000 characters of long-form input. The models are designed for reliable long-range information retrieval, with no noticeable degradation whether information appears at the beginning, middle, or end of the context.
    Starting Price: $0.0028 per 1M tokens