All AI tools
AI Large Language Models
This section brings together popular AI products for AI large language models, covering common use cases such as creation, processing, and efficiency enhancement.
Ling-3.2-flashAI Large Language ModelsLing-3.2-flash is the latest native multimodal large model launched by Ant Ling. It uses a Mixture-of-Experts (MoE) architecture with 560B total parameters and activates only about 25B per step. Its context window reaches 1M, with native support for image, text, and video inputs.00
SenseNova Loop-9B-PreviewAI Large Language ModelsSenseNova Loop-9B-Preview is SenseTime's open-source 9B-parameter multimodal preview model. It retains the original first and last four decoder layers, replaces the middle layers with parameter-shared recurrent computation modules, and ...00
Nemotron 3.5 TranscribeAI Large Language ModelsNemotron 3.5 Transcribe is NVIDIA’s open-source speech model, featuring a speech encoder plus MoE architecture with approximately 4.3 billion active parameters. It supports 40 languages and can process recordings up to 1 hour long with as many as 8 speakers...00
ClefAI Large Language ModelsClef is Cloudflare's open-source family of decision models. It sets the context, then decides what to do next. Unlike chat models that generate open-ended text, Clef temporarily defines the question in each request and scores each option...00
ZDTaichu5.0-9BAI Large Language ModelsZDTaichu5.0-9B is the new-generation general-purpose multimodal large model open-sourced by Zidong Taichu, designed for physical-world and embodied intelligence scenarios. The model ranked first globally among models with the same parameter count on 8 of 9 major international spatial benchmarks, scoring 7... on MindCube-tiny.00
MiniCPM5-2BAI Large Language ModelsMiniCPM5-2B is an on-device language foundation model jointly open-sourced by ModelBest, the OpenBMB community, and Tsinghua University. With approximately 2.5 billion parameters, it supports a 128K context and achieves an average score of 53.9 across 34 benchmarks, surpassing many 4B-class models and reaching 2...00
Spark X2.5AI Large Language ModelsSpark X2.5 is iFlytek's flagship general-purpose large model series, featuring cloud-based MoE base models (293B/30B) and open-source edge models, including Spark X2.5-4B and Spark X2.5-1.7B. The models are trained through an end-to-end process using fully domestic computing power...00
National Anti-Fraud AIAI Large Language ModelsNational Anti-Fraud AI is a telecom and online fraud prevention education platform guided by the Criminal Investigation Bureau of the Ministry of Public Security and independently developed by the Shanghai Public Security Bureau. The platform integrates large language models, multimodal models, and agent technology to provide AI-powered Q&A, anti-fraud news...00
E-Commerce BenchAI Large Language ModelsE-Commerce Bench is a long-horizon e-commerce operations benchmark open-sourced by Alibaba's Qwen team in collaboration with the Taotian Group. E-Commerce Bench lets an LLM Agent operate an online store with RMB 100,000 in starting capital in a simulated real-world market for 365 days,...00
Qwen 3.8-Max – The flagship large model launched by Alibaba Cloud’s Qwen teamAI Large Language ModelsQwen 3.8-Max – the flagship large model launched by Alibaba Cloud’s Qwen team, expanding the Qwen 3.5 architecture to 2.4 trillion parameters and positioned as an ultra-large language model for enterprise and research use. It supports long-horizon autonomous coding, paper reproduction, competition practice, workplace productivity, quantitative strategy development, and autonomous chip design. Through real-world reinforcement learning and a self-evolving feedback loop, the model can execute autonomously for days to tens of days and complete complex tasks without human intervention. Users can call it through APIs compatible with the OpenAI or Anthropic protocols on the Qwen AI platform, or deploy its open-source weights locally for easy integration with agent frameworks such as Claude Code, Codex, and Qoder. As a result, professional users in R&D, legal and compliance, design, and other fields can significantly improve productivity, compressing long-cycle projects into deliveries completed within a single conversation.00
SenseNova U1.5-Lite-Preview – SenseTime's Open-Source Lightweight Multimodal ModelAI Large Language ModelsSenseNova U1.5-Lite-Preview – SenseTime's open-source lightweight multimodal model is based on the NEO-Unify architecture. With 8B-MoT parameters, it natively unifies visual understanding, reasoning, generation, and editing. The model supports native 4K ultra-high-definition image generation, with fine textures, realistic details, and Chinese and English text rendering in complex layouts. Its built-in Prompt Enhance Skill lowers the barrier to creation, enabling precise execution of long natural-language and structured visual instructions, as well as continuous iterative editing. Designed for designers, developers, and content creators, it provides a commercial-grade visual creation tool with low deployment costs and strong instruction-following capabilities.00
SeedRealtime – ByteDance’s Native Audio-Visual Full-Duplex Foundation ModelAI Large Language ModelsSeedRealtime – ByteDance’s Native Audio-Visual Full-Duplex Foundation Model is a native audio-visual full-duplex foundation model developed by ByteDance’s Seed team. Built on a unified architecture that natively integrates audio, video, and text, it enables fully multimodal real-time interaction while seeing, listening, and speaking simultaneously. Its core capabilities include joint audio-visual understanding, proactive interaction, smooth conversational pacing, and multi-person scene recognition. It can use visual context to resolve homophone ambiguity, proactively alert users when the scene changes, distinguish side conversations from background noise in noisy environments, and continuously associate each person’s voice with their identity. The model uses end-to-end unified modeling and a native full-duplex interaction mechanism to avoid information loss and accumulated latency in cascaded systems. It is now fully deployed in the Doubao app, becoming the industry’s first audio-visual full-duplex AI product to achieve large-scale deployment.00
Ling-3.0-tiny – Ant Group's Ling native hybrid reasoning modelAI Large Language ModelsLing-3.0-tiny – Ant Group's Ling native hybrid reasoning model is a sparse Mixture-of-Experts (MoE) model with 7.9B total parameters and only approximately 1.3B parameters activated per token, designed to balance efficient computation with strong expressive capabilities. The model natively supports tool calling and can directly drive browser UI control and mobile device automation, while also supporting fully local inference without cloud dependencies. Its core advantages are extreme lightweightness, privacy-first operation, and native tool capabilities, making it particularly suitable for resource-constrained on-device and edge deployment scenarios. Typical applications include offline intelligent assistants on mobile devices, browser automation, local knowledge management (such as integration with obsidian-cli), and compliant AI services on enterprise intranets or industrial control computers.00All tools in this category are shown.