Image analysis

Kimi K3 is a 2.8 trillion parameter sparse Mixture-of-Experts language model with native vision understanding and a context window of up to 1 million tokens. It uses Kimi Delta Attention and Attention Residuals to improve long-context efficiency and depth scaling, with an always-on reasoning mode for coding, knowledge work, and agentic tool use.

💬Chatting 💻Coding 🤖Agents 🔍Research 📄Document analysis 🔍Image analysis

NewMultimodal

Released 7d ago

Gen 3

Inkling

By Thinking Machines Lab

Inkling is an open-weights Mixture-of-Experts transformer from Thinking Machines Lab with 975B total parameters (41B active) and native multimodal support for text, image, and audio input with text output. It supports up to a 1M-token context window and controllable reasoning effort, letting developers trade off cost and latency. Trained on 45 trillion tokens, it targets broad, balanced performance across reasoning, agentic coding, tool use, and multimodal tasks.

💬Chatting 💻Coding 🗒Transcription 🔍Image analysis

NewMultimodal

Released 8d ago

Gen 3

Bonsai 27B AWQ 4bit

By PrismML

Bonsai 27B AWQ 4bit is a 4-bit AWQ quantized release of Prism ML's Bonsai 27B, a 27 billion parameter multimodal model that accepts image and text input. It supports multi-step reasoning, tool calling, and agentic workflows, and is built for efficient deployment on inference engines like vLLM and SGLang.

💬Chatting 📷Images 🔍Image analysis

NewMultimodal

Released 8d ago

Gen 3 Qwen

Ternary Bonsai 27B AWQ 4bit

By PrismML

Ternary Bonsai 27B AWQ 4bit is a 4 bit AWQ quantized build of PrismML's Ternary Bonsai 27B, a multimodal model based on Qwen3.6 27B. It accepts text and images, supports a 262K token context window, and is designed for reasoning, coding, and agentic tool use workflows served efficiently via vLLM or SGLang.

💬Chatting 💡Coding help 🔍Image analysis

NewMultimodal

Released 9d ago

Gen 3

MOSS VL Realtime

By OpenMOSS

MOSS-VL-Realtime is an 11B parameter vision language model built for continuous video streams. It perceives incoming frames and generates text in parallel, answers questions asked at any point in the stream, and can stay silent or revise earlier answers as new visual evidence arrives. It uses a cross attention architecture with timestamp aware frame encoding and a 256K context window.

🎥Video analysis 📷Images 🎥Videos 🔍Image analysis 🔍Visual analysis

NewMultimodal

Released 9d ago

Gen 3

SenseNova Vision 7B MoT

By SenseTime

SenseNova-Vision-7B-MoT is a unified multimodal model for computer vision. It reformulates object detection, OCR, referring localization, GUI grounding, keypoint detection, depth estimation, surface normal prediction, segmentation, and multi-view geometry as text, image, or mixed text-image generation, using natural language instructions instead of separate task-specific heads or decoders for each vision task.

👁️Computer vision assistance 🔍Image recognition 🖼️Image segmentation 🔍Image analysis 📜OCR

NewMultimodal

Released 10d ago

Gen 3

Muse Spark 1.1

By Meta Platforms

Muse Spark 1.1 is a multimodal reasoning model built for agentic tasks, with strengths in tool use, computer use, coding, and multimodal understanding. It manages a 1 million token context window and orchestrates multi-agent systems for complex, long-running projects.

💬Chatting 🎥Video analysis 💻Coding 🤖Agents 🔍Image analysis

NewMultimodal

Released 14d ago

Gen 4 LingBot

LingBot Vision Giant

By Robbyant

LingBot-Vision-Giant is a ViT-g/16 self-supervised Vision Transformer backbone for dense visual perception. Pretrained with masked boundary modeling, a boundary-centric objective that produces spatially structured patch features while retaining strong semantic representations, intended for feature extraction and dense prediction research.

🔍Image analysis 🔍Image recognition 🖼️Image segmentation 🎥Video analysis 👁️Computer vision assistance

NewImage

Released 17d ago

Gen 4 LingBot

LingBot Vision Small

By Robbyant

LingBot-Vision-Small is a lightweight Vision Transformer (ViT-S/16) backbone pretrained with self-supervised masked boundary modeling for dense spatial perception. It produces boundary-aware patch token embeddings for feature extraction, PCA visualization, and downstream dense prediction tasks such as depth estimation and semantic segmentation.

🔍Image analysis 🖼️Image segmentation 👁️Computer vision assistance 📸Image data extraction

NewImage

Released 17d ago

Announcement Gen 3

Orca (BAAI)

By Beijing Academy of Artificial Intelligence (BAAI)

Orca is a world foundation model that learns a unified latent world state from multimodal signals to predict future states, rather than predicting next tokens, frames, or actions directly. It uses unconscious learning from continuous video and conscious learning from language described events to model physically consistent state transitions, which are read out through language, vision, and action interfaces.

🎥Video analysis 🔍Research 🔍Image analysis 🤖Robotics

NewMultimodal

Released 24d ago

Gen 3

Agnes 2.0 Flash

By Agnes AI

Agnes 2.0 Flash is a fast, cost efficient language model built for high frequency production use. It handles text generation, multi turn conversation, tool calling, coding assistance, agent workflows, and image understanding via image URLs, with an optional Thinking mode for deeper step by step reasoning on complex tasks.

💬Chatting 🤖Task automation 💻Coding 🤖Agents 🔍Image analysis

NewMultimodal

Released 1mo ago

Gen 3 Step

Step 3.7 Flash

By StepFun

StepFun's flagship multimodal reasoning model, a 198B total parameter sparse MoE with 11B active parameters. Natively understands images and video, supports adjustable reasoning effort, and is optimized for agent and coding workflows with reliable tool calling.

💬Chatting 🤖Task automation 🎥Video analysis 💻Coding 🤖Agents 🔍Image analysis

NewMultimodal

Released 1mo ago

Gen 3 GLM

GLM 4.6V FlashX

By Z.ai

Multimodal LLM with a 128K token context window accepting image, video, text, and file inputs with text output. The paid tier of the GLM-4.6V-Flash series offering higher capacity and stability. First visual model to natively integrate Function Call capability, enabling direct multimodal tool use without intermediate text conversion.

📝Text generation 🎥Video analysis 🔍Image analysis

Multimodal

Released 7mo ago

Gen 3 Phi

Phi 3 vision

By Gentext Group

Phi-3-Vision is Microsoft’s compact, open-weight multimodal model that understands images + text and answers in text. Optimized for documents, charts, UI screenshots, diagrams, and photos, it delivers strong OCR and visual reasoning in a small footprint suitable for single-GPU or edge deployment.

📷Images 🖼️Image to text ❓Answers 🔍Image analysis

Text

Released 10mo ago

Gen 4

DINOv3

By Meta Platforms

DINOv3 is a self supervised computer vision model from Meta that produces universal image backbones without using human labeled data. Trained up to 7 billion parameters on 1.7 billion images, it generates high resolution dense visual features that power tasks like object detection, image segmentation, depth estimation and video object tracking without any finetuning.

🔍Image analysis 🔍Image recognition 🖼️Image segmentation 🎥Video analysis

Image

Released 11mo ago

Gen 4

DINOv2

By Meta Platforms

DINOv2 is a self-supervised Vision Transformer developed by Meta AI that learns general-purpose visual features from unlabeled images. It produces class and patch token embeddings usable without fine-tuning for image classification, semantic segmentation, depth estimation, and image retrieval.

🔍Image analysis 🖼️Image segmentation 🔍Image search 🧩Pattern recognition

Image

Released 3y ago

Gen 4

NSFW Model

By Infinite Red

Image classification model trained on 60+ gigs of data to detect NSFW content. Classifies images into five categories: drawings, hentai, neutral, porn, and sexy. Built on Inception V3 and MobileNet V2 architectures with 93% accuracy.

🔍Image recognition 🔍Image analysis

Image

Released 6y ago