Past battle · 2026-04-23 UTC
Multimodal AI Showdown — April 23, 2026
From the Multimodal AI category. 44 marks placed across 9 fighters. AssiPilot took the crown.
Final standings
The line-up
The fighters
Profiles of every tool that competed in this battle, ranked by their final score.
AssiPilot is an all-in-one AI assistant designed to help create images, videos, voiceovers, and music. It aims to simplify the creative process for users by providing a chat-based interface where they can describe their ideas and receive the desired output. The platform is geared towards creators, including professionals and individuals, who need to produce high-quality content quickly and efficiently. AssiPilot aggregates various AI models, including Flux for images, Kling for video, and ElevenLabs for voice, to provide users with a range of capabilities. The workflow involves three main steps: chatting with AssiPilot to describe the desired content, selecting the appropriate tool, and generating and refining the output. Users can export their creations in high definition and own the commercial rights to the content they produce. AssiPilot's features include AI image, video, voice, and music generators. The platform supports multi-model capabilities, allowing users to access the latest state-of-the-art technology. It also offers integrated workflow tools, smart prompting, and cloud storage. According to the platform, thousands of creators have used AssiPilot to generate over 1 million assets. The platform has received positive feedback from users, who appreciate its ability to streamline their workflow and produce high-quality content quickly.
Criteria breakdown
- AI image generation
- AI video creation
- Text-to-speech voice generation
- AI music composition
- Unified creator dashboard
- Prompt-based content workflows
EmbedAI
Build custom ChatGPT-powered chatbots trained on your own data and embed them anywhere.
EmbedAI is a no-code platform for creating AI chatbots that respond using your own content. Users can upload documents, link websites, or connect other data sources, and the platform processes that information into a conversational assistant powered by large language models like ChatGPT. Once trained, the chatbot can be embedded on a website with a snippet of code or shared as a standalone link. It is commonly used for customer support, internal knowledge bases, lead capture, and interactive product documentation, helping teams reduce repetitive questions and surface information more efficiently.
Criteria breakdown
- Custom chatbot training on uploaded data
- Website and document ingestion
- Embeddable chat widget for any site
- Shareable chatbot links
- ChatGPT-powered conversational responses
- Multi-source knowledge base support
Magentic One
Open-source generalist multi-agent system for tackling complex, multi-step tasks
Magentic One is a research-oriented multi-agent framework from Microsoft designed to handle open-ended, complex tasks that span the web, files, and code. A lead Orchestrator agent plans, delegates, and tracks progress while specialized agents handle web browsing, file navigation, coding, and terminal execution. Built on top of the AutoGen framework, it offers a modular architecture that researchers and developers can extend or adapt to their own domains. It is intended as a baseline for studying agentic AI systems rather than a polished consumer product. Magentic One ships with an evaluation harness (AutoGenBench) so teams can benchmark agent performance on standardized tasks and compare different model backbones or agent configurations.
Criteria breakdown
- Orchestrator agent for planning and task tracking
- WebSurfer agent for browser-based actions
- FileSurfer agent for local file navigation
- Coder and ComputerTerminal agents for code tasks
- Built on the AutoGen multi-agent framework
- AutoGenBench integration for evaluation
Together AI
A cloud platform offering tools for building, fine-tuning, and deploying generative AI models with enhanced performance and cost efficiency.
Together AI offers a cloud platform for building, fine-tuning, and deploying generative AI models. The platform, powered by cutting-edge research, allows users to accelerate inference, model shaping, and pre-training with workload-specific optimization. Key features of the platform include serverless inference, batch inference, dedicated model inference, accelerated compute, sandbox, and managed storage. Additionally, there are tools for fine-tuning open-source models for production workloads, using the latest research techniques. The platform is built on the concept of AI-native cloud, which enables users to power every step of the AI development journey from experimentation to massive scale. Together AI's capabilities include improved inference performance, lowered costs, and faster pre-training. The platform also features cutting-edge research-driven kernels and tools for agent development, architecture, and fine-tuning.
Criteria breakdown
- Serverless Inference
- Batch Inference
- Dedicated Model Inference
- Dedicated Container Inference
- Accelerated Compute
- Sandbox
Omniverse Audio2Face
NVIDIA's AI-driven tool for generating real-time, voice-synced 3D facial animation
Omniverse Audio2Face is an NVIDIA application that automatically generates 3D facial animation from an audio source. Using a pre-trained deep neural network, it analyzes voice input and drives the facial expressions, lip sync, and emotion of a 3D character in real time, eliminating much of the manual keyframing typically required in animation pipelines. The tool runs inside NVIDIA Omniverse and supports export to standard DCC platforms like Maya, Unreal Engine, and Blender through formats such as USD and blendshapes. It works with custom character meshes via a retargeting workflow, making it useful for game developers, animators, virtual production teams, and creators building digital humans or interactive avatars. Audio2Face supports both offline processing for cinematic work and live streaming for interactive applications, with adjustable emotion controls and multilingual audio handling.
Criteria breakdown
- Audio-driven facial animation via deep learning
- Real-time lip sync and emotion control
- Character retargeting to custom meshes
- Blendshape and USD export pipelines
- Live streaming mode for interactive avatars
- Multilingual voice input support
AGiXT
Open-source AI agent framework with adaptive memory and extensible plugins for automating complex tasks.
AGiXT is an open-source AI agent framework that enables automation of complex tasks through adaptive memory and extensible plugins. It allows users to set up an AI agent with customizable personality, knowledge domain, and memory. The framework supports various document types for training, including PDF, Word, Text, Markdown, CSV, JSON, and Excel. Users can interact with the agent via a chat interface, and the agent can learn from provided documents and URLs.
Criteria breakdown
- Adaptive long-term memory
- Plugin and extension ecosystem
- Multi-provider LLM support
- Custom prompt and chain management
- Web UI and REST API
- Task automation with autonomous agents
Blink AI: Your Instant Shopping Guide
AI shopping assistant for instant product picks and price comparisons.
Blink AI is an artificial intelligence-powered shopping assistant designed to provide users with instant product recommendations and price comparisons. It aims to simplify the online shopping experience by quickly suggesting relevant products based on user inputs or preferences. The tool is intended for consumers looking for efficient and personalized shopping assistance. Blink AI likely operates by processing user queries, accessing a database of products, and then offering matches based on the information provided. Its standout capability appears to be the speed and accuracy of its product suggestions and price comparisons, though specific details on its workflow and integrations are not available. Compared to traditional shopping methods or other AI shopping tools, Blink AI focuses on immediacy and user-specific recommendations.
Criteria breakdown
- AI-powered product suggestions
- Instant multi-retailer price comparison
- Personalized shopping guidance
- Quick search across product categories
- Deal and discount surfacing
- Streamlined buying decision workflow
Project Astra
Google DeepMind's universal AI agent that sees, hears, and reasons about the world in real time.
Project Astra is an experimental universal AI assistant from Google DeepMind designed to help with everyday tasks by understanding the world the way people do. It processes video, audio, images, and text simultaneously, allowing users to point a camera or speak naturally and receive context-aware responses. Built on Google's Gemini models, Astra is engineered for low-latency, conversational interaction with persistent memory of recent context. It is positioned as a research prototype exploring how a general-purpose agent could eventually run across phones, smart glasses, and other ambient devices. While not yet a publicly available product, Astra signals Google's direction for agentic AI that can observe surroundings, recall what it has seen, and take helpful actions on a user's behalf.
Criteria breakdown
- Live video and image comprehension
- Voice-based conversational interface
- Persistent contextual memory
- Multimodal reasoning across text, audio, and visuals
- Integration with Gemini model family
- Prototype support for smart glasses and phones
Wan 2.7
An AI video and image generation platform for turning prompts or images into commercial-ready visual content.
Wan 2.7 is an AI video and image generation platform that upgrades visual quality, audio, motion, stylization, and consistency compared to its predecessor, Wan 2.6. It is designed for turning prompts or images into commercial-ready visual content. The platform improves video generation across five key areas: visual quality, audio, motion dynamics, stylization, and consistency. Wan 2.7 adds features such as first-frame and last-frame generation, 9-grid image-to-video, subject plus voice reference, instruction-based editing, and video recreation. It supports real-person image input, up to 5 video references, 2-15 second duration, and 1080P video generation, making it suitable for professional workflows. The platform is aimed at end-to-end video creation and editing, offering better control and quality.
Criteria breakdown
- First-frame and last-frame generation
- 9-grid image-to-video
- Subject plus voice reference
- Instruction-based editing
- Video recreation
- Up to 5 video references