Best Multimodal AI Models
12 models tracked · 60 recent news stories
Most-talked-about Multimodal right now
Ranked by mentions across 30+ AI sources in August 2026.
Amazon Nova — Amazon's family of foundation models on AWS Bedrock, spanning text, vision and the Nova Act agentic browser model.
NVIDIA Cosmos — world foundation models that generate physics-aware synthetic data and reasoning for physical AI and robotics.
NVIDIA's foundation model for humanoid robots (Isaac GR00T), enabling generalist embodied skills.
Gemini 3.1 Pro — Google's frontier Gemini model for complex reasoning tasks, benchmarked against GPT-5.4, Claude Opus 4.6 and Grok.
Google DeepMind's embodied-reasoning Gemini model for real-world robotics tasks.
Google DeepMind's most capable open model family. Available in 4 sizes (E2B, E4B, 26B MoE, 31B Dense) with advanced reasoning, agentic workflows, vision, audio, 256K context, 140+ languages. Apache 2.0 license. Runs on devices from phones to H100 GPUs.
Inkling — Thinking Machines Lab's first model trained from scratch: a 975B-parameter open-weights multimodal Mixture-of-Experts with 41B active parameters and controllable thinking effort, released under Apache 2.0 in July 2026.
ByteDance's unified model for image and video understanding, generation and editing.
Mistral AI's document-intelligence (OCR) model (June 2026). Structure-aware extraction with bounding boxes, block classification and confidence scores across 170 languages; self-hostable in a single container. Tops OlmOCRBench; feeds RAG, agentic and enterprise-search pipelines.
Step 3.7 — StepFun's enterprise-ready multimodal model (including the Step 3.7 Flash tier), optimised for NVIDIA GPU inference.
Physical Intelligence's Vision-Language-Action (VLA) models for general robot control (π0, π0-FAST, π0.6).
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