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Qwen 3 is the latest large reasoning model developed by Alibaba company. It surpass multiple baselines on coding, math and surpass SOTA model performance on multiple benchmarks. It is said to be released by May, 2025. # Qwen3 Qwen Chat | Hugging Face | ModelScope | Paper | Blog ｜ Documentation Demo | WeChat (微信) | Discord Visit our Hugging Fac
## Google Gemini Flash Nano Banana Today, we’re excited to introduce Gemini 2.5 Flash Image (aka nano-banana), our state-of-the-art image generation and editing model. This update enables you to blend multiple images into a single image, maintain character consistency for rich storytelling, make targeted transformations using natural language, and use Gemini's world knowledge to generate and ed
Qwen3 Highlights Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models. Built upon extensive training, Qwen3 delivers groundbreaking advancements in reasoning, instruction-following, agent capabilities, and multilingual support, with the following key features: # Qwen3-235B-A22B ## Qw
# Qwen3-Coder-480B-A35B-Instruct ## Highlights Today, we're announcing **Qwen3-Coder**, our most agentic code model to date. **Qwen3-Coder** is available in multiple sizes, but we're excited to introduce its most powerful variant first: **Qwen3-Coder-480B-A35B-Instruct**. featuring the following key enhancements: - **Significant Performance** among open models on **Agentic Cod
--- license: mit library_name: LongCat-Flash-Chat pipeline_tag: text-generation tags: - transformers --- # LongCat-Flash-Chat ## Model Introduction We introduce LongCat-Flash, a powerful and efficient language model with 560 billion total parameters, featuring an innovative Mixture-of
Claude Opus 4 is the Hybrid reasoning model that pushes the frontier for coding and AI agents, featuring a 200K context window Claude Opus 4 is our most intelligent model to date, pushing the frontier in coding, agentic search, and creative writing. We’ve also made it possible to run Claude Code in the background, enabling developers to assign long-running coding tasks for Opus to handle indepe
Anthropic launched the next generation of Claude models today—Opus 4 and Sonnet 4—designed for coding, advanced reasoning, and the support of the next generation of capable, autonomous AI agents. Claude 4 hybrid reasoning models let customers choose between near-instant responses and deeper reasoning. Claude 4 models offer improvements in coding, with Opus 4 as the “world’s best coding model
Qwen3-0.6B has the following features: Type: Causal Language Models Training Stage: Pretraining & Post-training Number of Parameters: 0.6B Number of Paramaters (Non-Embedding): 0.44B Number of Layers: 28 Number of Attention Heads (GQA): 16 for Q and 8 for KV Context Length: 32,768 # Qwen3-0.6B ## Qwen3 Highlights Qwen3 is the latest generation of large language models
Qwen3-32B has the following features: Type: Causal Language Models Training Stage: Pretraining & Post-training Number of Parameters: 32.8B Number of Paramaters (Non-Embedding): 31.2B Number of Layers: 64 Number of Attention Heads (GQA): 64 for Q and 8 for KV Context Length: 32,768 natively and 131,072 tokens with YaRN. # Qwen3-32B ## Qwen3 Highlights Qwen3 is the late
Deepseek R2 is the latest large reasoning model developped by the Deepseek company. It surpasses multiple baselines on coding, math benchmarks and lower the training as well as the inference cost by 95%. It is said to be released by May, 2025.
Tech Blog | Paper Link (coming soon) ## 1. Model Introduction Kimi K2 is a state-of-the-art mixture-of-experts (MoE) language model with 32 billion activated parameters and 1 trillion total parameters. Trained with the Muon optimizer, Kimi K2 achieves exceptional performance across frontier knowledge, reasoning, and coding t
DeepSeek-Prover-V2 is an open-source large language model designed for formal theorem proving in Lean 4, with initialization data collected through a recursive theorem proving pipeline powered by DeepSeek-V3. The cold-start training procedure begins by prompting DeepSeek-V3 to decompose complex problems into a series of subgoals. The proofs of resolved subgoals are synthesized into a chain-of-thou
Hybrid reasoning model with superior intelligence for high-volume use cases, and 200K context window Claude Sonnet 4 improves on Claude Sonnet 3.7 across a variety of areas, especially coding. It offers frontier performance that’s practical for most AI use cases, including user-facing AI assistants and high-volume tasks. Claude Sonnet 3.7 is the first hybrid reasoning model and our most inte
## OpenAI just released their flagship video and audio model Sora 2 You can download the apps from app store: https://apps.apple.com/us/app/sora-by-openai/id6744034028 ## Introduction The original Sora model from February 2024 was in many ways the GPT‑1 moment for video—the first time video generation started to seem like it was working, and simple behaviors like object permanence emer
## Main Features It's the strongest model for building complex agents. It’s the best model at using computers. And it shows substantial gains in reasoning and math. Code is everywhere. It runs every application, spreadsheet, and software tool you use. Being able to use those tools and reason through hard problems is how modern work gets done. Claude Sonnet 4.5 makes this possible. We're r
Meet Qwen3-VL — the most powerful vision-language model in the Qwen series to date. This generation delivers comprehensive upgrades across the board: superior text understanding & generation, deeper visual perception & reasoning, extended context length, enhanced spatial and video dynamics comprehension, and stronger agent interaction capabilities. Available in Dense and MoE architectures th
Qwen3 14B has the following features: - Type: Causal Language Models - Training Stage: Pretraining & Post-training - Number of Parameters: 14.8B - Number of Paramaters (Non-Embedding): 13.2B - Number of Layers: 40 - Number of Attention Heads (GQA): 40 for Q and 8 for KV - Context Length: 32,768 natively and . # Qwen3-14B ## Qwen3 Highlights Qwen3 is the latest generati
Qwen3-8B has the following features: Type: Causal Language Models Training Stage: Pretraining & Post-training Number of Parameters: 8.2B Number of Paramaters (Non-Embedding): 6.95B Number of Layers: 36 Number of Attention Heads (GQA): 32 for Q and 8 for KV Context Length: 32,768 natively and 131,072 tokens with YaRN. # Qwen3-8B ## Qwen3 Highlights Qwen3 is the latest
REASON
Qwen 3 is the latest large reasoning model developed by Alibaba company. It surpass multiple baselines on coding, math and surpass SOTA model performance on multiple benchmarks. It is said to be released by May, 2025. # Qwen3 Qwen Chat | Hugging Face | ModelScope | Paper | Blog ｜ Documentation Demo | WeChat (微信) | Discord Visit our Hugging Fac
Deepseek R2 is the latest large reasoning model developped by the Deepseek company. It surpasses multiple baselines on coding, math benchmarks and lower the training as well as the inference cost by 95%. It is said to be released by May, 2025.
Claude Opus 4 is the Hybrid reasoning model that pushes the frontier for coding and AI agents, featuring a 200K context window Claude Opus 4 is our most intelligent model to date, pushing the frontier in coding, agentic search, and creative writing. We’ve also made it possible to run Claude Code in the background, enabling developers to assign long-running coding tasks for Opus to handle indepe
Qwen3-32B has the following features: Type: Causal Language Models Training Stage: Pretraining & Post-training Number of Parameters: 32.8B Number of Paramaters (Non-Embedding): 31.2B Number of Layers: 64 Number of Attention Heads (GQA): 64 for Q and 8 for KV Context Length: 32,768 natively and 131,072 tokens with YaRN. # Qwen3-32B ## Qwen3 Highlights Qwen3 is the late
DeepSeek-Prover-V2 is an open-source large language model designed for formal theorem proving in Lean 4, with initialization data collected through a recursive theorem proving pipeline powered by DeepSeek-V3. The cold-start training procedure begins by prompting DeepSeek-V3 to decompose complex problems into a series of subgoals. The proofs of resolved subgoals are synthesized into a chain-of-thou
Anthropic launched the next generation of Claude models today—Opus 4 and Sonnet 4—designed for coding, advanced reasoning, and the support of the next generation of capable, autonomous AI agents. Claude 4 hybrid reasoning models let customers choose between near-instant responses and deeper reasoning. Claude 4 models offer improvements in coding, with Opus 4 as the “world’s best coding model
Qwen3-0.6B has the following features: Type: Causal Language Models Training Stage: Pretraining & Post-training Number of Parameters: 0.6B Number of Paramaters (Non-Embedding): 0.44B Number of Layers: 28 Number of Attention Heads (GQA): 16 for Q and 8 for KV Context Length: 32,768 # Qwen3-0.6B ## Qwen3 Highlights Qwen3 is the latest generation of large language models
Hybrid reasoning model with superior intelligence for high-volume use cases, and 200K context window Claude Sonnet 4 improves on Claude Sonnet 3.7 across a variety of areas, especially coding. It offers frontier performance that’s practical for most AI use cases, including user-facing AI assistants and high-volume tasks. Claude Sonnet 3.7 is the first hybrid reasoning model and our most inte
Qwen3 14B has the following features: - Type: Causal Language Models - Training Stage: Pretraining & Post-training - Number of Parameters: 14.8B - Number of Paramaters (Non-Embedding): 13.2B - Number of Layers: 40 - Number of Attention Heads (GQA): 40 for Q and 8 for KV - Context Length: 32,768 natively and . # Qwen3-14B ## Qwen3 Highlights Qwen3 is the latest generati
Qwen3-1.7B has the following features: Type: Causal Language Models Training Stage: Pretraining & Post-training Number of Parameters: 1.7B Number of Paramaters (Non-Embedding): 1.4B Number of Layers: 28 Number of Attention Heads (GQA): 16 for Q and 8 for KV Context Length: 32,768 # Qwen3-1.7B ## Qwen3 Highlights Qwen3 is the latest generation of large language models in
Qwen3-4B has the following features: Type: Causal Language Models Training Stage: Pretraining & Post-training Number of Parameters: 4.0B Number of Paramaters (Non-Embedding): 3.6B Number of Layers: 36 Number of Attention Heads (GQA): 32 for Q and 8 for KV Context Length: 32,768 natively and 131,072 tokens with YaRN. # Qwen3-4B ## Qwen3 Highlights Qwen3 is the latest gen
Qwen3-8B has the following features: Type: Causal Language Models Training Stage: Pretraining & Post-training Number of Parameters: 8.2B Number of Paramaters (Non-Embedding): 6.95B Number of Layers: 36 Number of Attention Heads (GQA): 32 for Q and 8 for KV Context Length: 32,768 natively and 131,072 tokens with YaRN. # Qwen3-8B ## Qwen3 Highlights Qwen3 is the latest
MULTI MODAL
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大家在使用可灵AI生成视频的时候遇到了哪些好的体验和有问题的体验？请务必写明prompt输入文本和视频截图or短视频clip
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大家在使用抖音的即梦AI生成视频的时候遇到了哪些好的体验和有问题的体验？请务必写明prompt输入文本和视频截图or短视频clip
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大家在使用快手(Kuaishou Kwai)短视频的搜索推荐Search and Recommendation 功能的时候遇到了哪些好的体验和有问题的体验？请麻烦写明复现条件，比如prompt输入文本，上传截图。
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大家在使用小红书(Xiaohongshu)APP的搜索推荐Search and Recommendation 功能的时候遇到了哪些好的体验和有问题的体验？请麻烦写明复现条件，比如prompt输入文本，上传截图。
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大家在使用微信(WeChat)APP的搜索推荐Search and Recommendation 功能的时候遇到了哪些好的体验和有问题的体验？请麻烦写明复现条件，比如prompt输入文本，上传截图。
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大家在使用微信(WeChat)APP的AI问答功能的时候，遇到了哪些好的体验和有问题的体验？请麻烦写明复现条件，比如prompt输入文本，上传截图。
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大家在使用知乎(Zhihu)APP的搜索推荐Search and Recommendation 功能的时候遇到了哪些好的体验和有问题的体验？请麻烦写明复现条件，比如prompt输入文本，上传截图。
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大家在使用京东(JD)APP的搜索推荐Search and Recommendation 功能的时候遇到了哪些好的体验和有问题的体验？请麻烦写明复现条件，比如prompt输入文本，上传截图。
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大家在使用淘宝(Taobao)APP的搜索推荐Search and Recommendation 功能的时候遇到了哪些好的体验和有问题的体验？请麻烦写明复现条件，比如prompt输入文本，上传截图。
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大家在使用支付宝(Alipay)APP的搜索推荐Search and Recommendation 功能的时候遇到了哪些好的体验和有问题的体验？请麻烦写明复现条件，比如prompt输入文本，上传截图。
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大家在使用拼多多(PPD Temu)APP的搜索推荐Search and Recommendation 功能的时候遇到了哪些好的体验和有问题的体验？请麻烦写明复现条件，比如prompt输入文本，上传截图。
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大家在使用知乎直答(Zhihu)AI搜索功能的时候，遇到了哪些好的体验和有问题的体验？请麻烦写一下当时输入的条件，比如prompt输入文本，或者是上传截图。
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大家在使用知乎直答(Zhihu)AI搜索功能的时候，遇到了哪些好的体验和有问题的体验？请麻烦写一下当时输入的条件，比如prompt输入文本，或者是上传截图。
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大家在使用快手(Kuaishou)的AI搜索功能的时候，遇到了哪些好的体验和有问题的体验？请麻烦写一下当时输入的条件，比如prompt输入文本，或者是上传截图。
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大家在使用抖音(Douyin Tiktok)的AI搜索功能的时候，遇到了哪些好的体验和有问题的体验？请麻烦写一下当时输入的条件，比如prompt输入文本，或者是上传截图。
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We are witnessing great success in recent development of generative Artificial Intelligence in many fields, such as AI assistant, Chatbot, AI Writer. Among all the AI native products, AI Search Engine such as Perplexity, Gemini and SearchGPT are most attrative to website owners, bloggers and web content publishers. AI Search Engine is a new tool to provide answers directly to users' questions (queries). In this blog, we will give some brief introduction to basic concepts of AI Search Engine, including Large Language Models (LLM), Retrieval-Augmented Generation(RAG), Citations and Sources. Then we will highlight some majors differences between traditional Search Engine Optimization (SEO) and Generative Engine Optimization(GEO). And then we will cover some latest research and strategies to help website owners or content publishers to better optimize their content in Generative AI Search Engines.
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We are seeing more applications of robotaxi and self-driving vehicles worldwide. Many large companies such as Waymo, Tesla and Baidu are accelerating their speed of robotaxi deployment in multiple cities. Some human drivers especially cab drivers worry that they will lose their jobs due to AI. They argue that the lower operating cost and AI can work technically 24 hours a day without any rest like human will have more competing advantage than humans. What do you think?