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“OmniSVG announced on Hugging Face A Unified Scalable Vector Graphics Generation Model https://x.com/_akhaliq/status/1909935266069938653
“22/ @ferdousbhai built a new LLM client that runs in your terminal, supports all the models with your own api key and custom functions via Model Context Protocol. Less than 250 lines of code, made possible thanks to @Pydantic_AI and @textualizeio https://x.com/AtomSilverman/status/1910057879656448041
Arabic Leaderboards: Introducing Arabic Instruction Following, Updating AraGen, and More https://huggingface.co/blog/leaderboard-3c3h-aragen-ifeval
“LangGraph Python now supports Generative UI!” / X https://x.com/LangChainAI/status/1908186508969783495
“Understanding multi-agent handoffs Handoffs are a central concept in multi-agent systems. LangGraph swarm is built on them. But, they can be hard to understand. Here, we break-down the swarm handoff mechanism. 📽️: https://x.com/LangChainAI/status/1907828277940727911
“@AgentOpsAI 4/ AI Agents in Production: Insights and Future Directions Hosted by: Harrison Chase, Co-Founder and CEO, LangChain Key lessons covered will be from LangChain’s experience enabling customers to develop, deploy, and manage enterprise AI agents in production at scale, and will” / X https://x.com/AtomSilverman/status/1907898181196910973
“2025 might be the year of agents! But how do they work and how can i get started? Excited to share a new guide on how to build a ReAct Agent from scratch using @GoogleDeepMind Gemini 2.5 Pro and @LangChainAI LangGraph! ReACT (Reasoning and Acting) Agents are AI systems that https://x.com/_philschmid/status/1906699328292282475
“🤖 📚 ReAct Agent Tutorial Series Learn to build production AI agents with LangGraph and Tavily AI in this step-by-step guide, covering everything from basic implementation to advanced memory optimization and storage. Build your AI agent today! 👉 https://x.com/LangChainAI/status/1908203029385343414
“InternVL3 is out 💥 > 7 ckpts with various sizes (1B to 78B) > Built on InternViT encoder and Qwen2.5VL decoder, improves many points on Qwen2.5VL > Can do reasoning, document tasks, extending to tool use and agentic capabilities 🤖 > easily use with transformers 🤗 https://x.com/mervenoyann/status/1910687031505674706
“✨ AppFolio’s copilot, Realm-X — powered by LangGraph and LangSmith — saves property managers over 10 hours per week ✨ Realm-X Assistant is an AI copilot designed to streamline property managers’ daily tasks. It offers a conversational interface that empowers users to https://x.com/LangChainAI/status/1908240852541202623
“🤖📚 DeepSeek-R1 Guide Learn to build RAG applications with DeepSeek-R1, an open-source alternative to OpenAI. This guide demonstrates local and cloud implementations using LangChain’s document processing tools. Check out the full guide: https://x.com/LangChainAI/status/1909274972339454227
“We’re excited to introduce a brand-new layout agent within LlamaParse that gives you the best-in-class document parsing and extraction with precise visual citations. It uses SOTA VLM models to 1) detect all the blocks on a page (tables/charts/paragraphs), and 2) dynamically https://x.com/llama_index/status/1909264185034506590
“Happy to share that weā€™ve just signed a ā‚¬100 million partnership with @cmacgm! @MistralAI is going to help CMA CGM adopt custom-designed AI solutions to support its shipping, logistics, and media activities. We will provide CMA CGM with our entire AI solutions portfolio and we https://x.com/sophiamyang/status/1909243949920768497
“Deep Cogito emerged from stealth with a mission to build “general superintelligence” The startup also launched Cogito v1 Preview, a family of open-source models that it claims beats the best available open-source models of the same size https://x.com/rowancheung/status/1909845137007530275
“We evaluated Llama 4 ourselves: On GPQA Diamond, Maverick and Scout scored 67% and 52%, similar to Meta’s reported 57% and 69.8%. On MATH Level 5, Maverick and Scout got 73% and 62%. Maverick is competitive with leading open or low-cost models, and both outperform Llama 3. https://x.com/EpochAIResearch/status/1909700016249479506
“Llama 4 analysis v1: 1. Maverick mixes MoE layers & dense – every odd MoE 2. Scout uses L2 Norm on QK (not QK Norm) 3. Both n_experts = 1 4. Official repo uses torch.bmm (not efficient) 5. Maverick layers 1, 3, 45 MoE are “special” layers 6. 8192 chunked attention Details: 1. https://x.com/danielhanchen/status/1909726119500431685
“Llama 4 is here! Meta has released two smaller versions of its new Llama 4 family of models: Llama 4 Scout and Maverick, and announced a larger version called Behemoth that is still in training. In this thread, we dig into their training details and benchmark performance 🧵” / X https://x.com/EpochAIResearch/status/1909699970594394173
“Llama 4 independent tests suggest a Maverick is very solid model, but not enough to beat DeepSeek v3 (non-reasoner version), though size-performance trade-offs make it hard to do exact comparisons.” / X https://x.com/emollick/status/1909632109964108285
“Llama-4 doesn’t disappoint! My notes: – Ease of deployment is now a more important OSS feature than sheer size. There’s emphasis that Llama 4 Scout can run on a single H100, as opposed to Llama-3-401B, which was powerful but ultimately had lesser adoption. Mixture of Expert is a https://x.com/DrJimFan/status/1908615861650547081
“You’re being unfair in a few ways. I disagree that: 1. “The soul of the Llama series died by not releasing enough models frequently enough.” Better to have fewer, better releases than more worse releases. It’s an impossible balance; I prefer Meta’s strategy to what you suggest.” / X https://x.com/jefrankle/status/1909244633764261987
“NEW: Llama 3.1 Nemotron Ultra 253B – beats Llama 4 Behemouth, Maverick & competitive with DeepSeek R1 – Commercially permissive! 🔥🔥🔥 > Open weights on the hub! https://x.com/reach_vb/status/1909584596401815691
“We’ve seen questions from the community about the latest release of Llama-4 on Arena. To ensure full transparency, we’re releasing 2,000+ head-to-head battle results for public review. This includes user prompts, model responses, and user preferences. (link in next tweet) Early” / X https://x.com/lmarena_ai/status/1909397817434816562
“New free & open source Together AI example app! Screenshot -> code powered by Llama 4. https://x.com/togethercompute/status/1910369366056882217
“Llama-4 Maverick on BigCodeBench-Full 61.9% Complete 49.7% Instruct Average 55.8% Both GPT-4o-2024-05-13 & DeepSeek V3 got 56.1% on average. There may be some gaps between Llama-4 Maverick and the recent (3-month) frontier models, given the fast pace in AI development these” / X https://x.com/terryyuezhuo/status/1909275015511687179
“We’ve linearized the experts in Llama-4 Scout; you can now fine-tune w/ 2x48GB GPUs @ 4k context. (adapters on self attention and shared experts). 8k context + adapters on experts uses only 2x53GB Support for linearized Llama-4 now in Axolotl OSS v0.8.1. Details & Model in 🧵” / X https://x.com/winglian/status/1909413876669558967
“@UnslothAI Smaller Llama size, same Llama power 💪 Absolutely stoked to see what the world builds with Llama 4” / X https://x.com/AIatMeta/status/1910010433576264036
“Today is the start of a new era of natively multimodal AI innovation. Today, we’re introducing the first Llama 4 models: Llama 4 Scout and Llama 4 Maverick — our most advanced models yet and the best in their class for multimodality. Llama 4 Scout • 17B-active-parameter model https://x.com/AIatMeta/status/1908598456144531660
“Some carifications about Llama-4.” / X https://x.com/ylecun/status/1909313264460378114
“chat, Llama 4 is so back! – with some more thoughtful post-training, we’ve got a pretty strong model here! 🔥 https://x.com/reach_vb/status/1909658152234033200
“We’re glad to start getting Llama 4 in all your hands. We’re already hearing lots of great results people are getting with these models. That said, we’re also hearing some reports of mixed quality across different services. Since we dropped the models as soon as they were” / X https://x.com/Ahmad_Al_Dahle/status/1909302532306092107
“The Llama 4 model that won in LM Arena is different than the released version. I have been comparing the answers from Arena to the released model. They aren’t close. The data is worth a look also as it shows how LM Arena results can be manipulated to be more pleasing to humans. https://x.com/emollick/status/1909414182962790467
“Just built a Llama 4 company researcher 🌐 Ask any information about a company then it will search the web and extract structured data for you using Firecrawl’s new /extract endpoint. Built with Meta’s new Llama 4 Maverick Model, @togethercompute, and @firecrawl_dev. https://x.com/nickscamara_/status/1910361430970515787
“The power of Llama 4 🤝 The simplicity of Vertex AI What will you build?” / X https://x.com/AIatMeta/status/1910034596638646584
“Llama 4 just released with a 10M context window. You could fit the entire Harry Potter series, A Song of Ice and Fire (Books 1–5), The Lord of the Rings, The Hobbit, The Bible, The Quran, and Dune. Still with millions of tokens to spare. This is library-scale reasoning. https://x.com/skirano/status/1908613559069635032
“Llama 4 Intelligence Index Update: We have now replicated Meta’s claimed values for MMLU Pro and GPQA Diamond, pushing our Intelligence Index scores for both Scout and Maverick higher Key update details: ➤ We noted in our first post 48 hours ago that we noticed discrepancies https://x.com/ArtificialAnlys/status/1909624239747182989
“See that purple banner on the Llama 4 models? It’s Xet storage, and this is actually huge for anyone building with AI models. With models getting bigger and downloads exploding, Git LFS is becoming less practical. Xet lets you version large files like code, with compression and https://x.com/fdaudens/status/1908646412125941989
“3 important updates from last week: 1. @AIatMeta’s surprise Saturday release of the Llama 4 herd: It sparked initial hype, quickly followed by widespread criticism. While mixture-of-experts (MoE) architecture allows for massive parameter counts, users report underwhelming https://x.com/TheTuringPost/status/1909933246823223668
“Llama 4 Scout is now live on the @vercel AI SDK Playground. Bewildering how fast @groqinc serves it. https://x.com/rauchg/status/1908616519430631552
“Hopefully the Llama 4 models improve rapidly, as they did in the Llama 3 generation. The initial launch got pretty mixed feedback (including from me) but a good open weights model from Meta would be very useful for many people.” / X https://x.com/emollick/status/1909306675174977637
“Me (earlier this year0): “Llama models aren’t optimized for production.” Meta: “Bet. Here’s the Llama 4 suite, MoE models with 16 & 128 experts” Me: “Yeah… maybe dense wasn’t so bad after all.”” / X https://x.com/rasbt/status/1909041971970072707
“Run Llama 3.2 from scratch – smol PyTorch implementation of Llama 3.2 text models with minimal code dependencies ⚡ by @rasbt on Hugging Face 🤗 https://x.com/reach_vb/status/1910353750746681805
“This is the clearest evidence that no one should take these rankings seriously. In this example it’s super yappy and factually inaccurate, and yet the user voted for Llama 4. The rest aren’t any better. https://x.com/vikhyatk/status/1909403603409969533
The Llama 4 herd: The beginning of a new era of natively multimodal AI innovation https://ai.meta.com/blog/llama-4-multimodal-intelligence/
“Pretty impressive outcomes in the leaderboard as well for Llama 4.” / X https://x.com/emollick/status/1908625383257436165
“@omarsar0 have you tested llama 4? It’s generating slop for me, but some saying it’s good.” / X https://x.com/Yuchenj_UW/status/1909062763789566100
“👀 Curious about Llama 4? Jump into Smol Arena and test it yourself! Play around with any AI model under 30B – no fancy stuff needed. Come geek out with us! 🤖” / X https://x.com/fdaudens/status/1909707381933568036
“We are excited to partner with @AIatMeta to welcome Llama 4 Maverick (402B) & Scout (109B) natively multimodal Language Models on the Hugging Face Hub with Xet 🤗 Both MoE models trained on up-to 40 Trillion tokens, pre-trained on 200 languages and significantly outperforms its https://x.com/huggingface/status/1908600868074639806
“🎊 Llama Nemotron Ultra 253B is here 🎊 ✅ 4x higher inference throughput over DeepSeek R1 671B 🏆Highest accuracy on reasoning benchmarks: 💎 GPQA-Diamond for advanced scientific reasoning 💎 AIME 2024/25 for complex math 💎 LiveCodeBench for code generation and completion https://x.com/NVIDIAAIDev/status/1909742262814490840
“If Meta actually did this for Llama 4 training to maximize benchmark scores, it’s fucked. https://x.com/Yuchenj_UW/status/1909061004207816960
“Gemini 2.5 Pro and Llama-4 results on Tic-Tac-Toe-Bench! playing as O (depends more on generalization) – Gemini 2.5 Pro is the 6th best model, but surprisingly worse than all the other frontier thinking models! – Llmao-4 Maverick scores below both Llama-3 70B versions because https://x.com/scaling01/status/1909028821396836369
“Meta announced three MoE-based Llama 4 models: 109B param Scout, 400B param Maverick, and 2T param Behemoth (in training) Scout features a 10M context window and beats Gemma 3 & Mistral 3 Maverick, with a 1M window, outperforms GPT-4o and Gemini 2.0 https://x.com/rowancheung/status/1909154238464147838
“Llama-4 Series on BigCodeBench-Hard *Inference via NVIDIA NIM Llama-4 Maverick Ranked 41th/192 Similar to Gemini-2.0-Flash-Thinking & GPT-4o-2024-05-13 29.1% Complete 25% Instruct Llama-4-Scout Ranked 97th/192 16.9% Complete 16.9% Instruct Also, new visuals on the leaderboard! https://x.com/terryyuezhuo/status/1909247540379148439
nvidia/Llama-3_1-Nemotron-Ultra-253B-v1 · Hugging Face https://huggingface.co/nvidia/Llama-3_1-Nemotron-Ultra-253B-v1#evaluation-results
“DeepCoder: A Fully Open-Source 14B Coder at O3-mini Level From @togethercompute https://x.com/rohanpaul_ai/status/1909711599352660076
“💕 @ollama finally added supports for @MistralAI Small 3.1! Give it a try: `ollama run mistral-small3.1` https://x.com/sophiamyang/status/1909312680424251392
“DeepCoder-14B-Preview achieves 60.6% on LiveCodeBench and a 1936 score on CodeForces, performing on par with o3-mini (low) and o1 on competition-level coding tasks. Despite being trained solely on coding data, DeepCoder generalizes remarkably well to the math domain, reaching https://x.com/togethercompute/status/1909697131645903065
“NEW code model in town, DeepCoder 14B – beats O3 Mini, MIT licensed, works w/ vLLM, TGI, Transformers and more! 🔥 https://x.com/reach_vb/status/1909706239577329915
“Together AI dropped DeepCoder-14B, a new reasoning-capable coding AI —Matches o3-mini (low) and o1 on competition-level coding tasks —Also generalizes well to math, scoring 73.8% on AIME —Fully open-sourced with dataset, code, and training recipe https://x.com/rowancheung/status/1909845189008449868
“Announcing DeepCoder-14B – an o1 & o3-mini level coding reasoning model fully open-sourced! We’re releasing everything: dataset, code, and training recipe.🔥 Built in collaboration with the @Agentica_ team. See how we created it. 🧵 https://x.com/togethercompute/status/1909697122372378908
DeepCoder: A Fully Open-Source 14B Coder at O3-mini Level https://www.together.ai/blog/deepcoder
“Pusa is out on Hugging Face Thousands Timesteps Video Diffusion Model A single model that unlocks: • Text-to-Video • Image-to-Video • Start/End Frames to Video • Video Transitions • Video Extensions • Next-frame prediction • Novel sampling https://x.com/_akhaliq/status/1910350235156488360
“On vibes, I don’t think the currently released Llama 4 models are a big enough increase in capability that they definitively take the lead in open weights models from the main Chinese models (and open weights continues to lag frontier closed). Meta is still training, though.” / X https://x.com/emollick/status/1908921025057653175
“American open-source has fallen. It’s all on Google and China bros now 🫠 https://x.com/scaling01/status/1909165768874336620
unsloth/DeepSeek-R1-GGUF at main https://huggingface.co/unsloth/DeepSeek-R1-GGUF/tree/main/DeepSeek-R1-UD-IQ1_S
“Looks interesting! The twitter thread forgot to mention the base model, which is deepseek-qwen — so many thanks to the qwen and deepseek teams too. :D” / X https://x.com/jeremyphoward/status/1909705022935646541
“Open source model weights here: https://x.com/reach_vb/status/1909706444028670311
QVQ-Max: Think with Evidence | Qwen https://qwenlm.github.io/blog/qvq-max-preview/
“DeepSeek-R1 is underrated” / X https://x.com/scaling01/status/1909304510075318318
“The absolute largest reasoning coding dataset just dropped in @huggingface A dataset of 736,712 DeepSeek-R1 generated code solutions (in Python) with reasoning traces, Ready for commercial/non-commercial use. https://x.com/rohanpaul_ai/status/1909602083923485168
“Scaling reasoning capabilities in LLMs using complex Reinforcement Learning (RL) methods lacks open, simple implementations. Open-Reasoner-Zero presents an accessible, open-source RL approach. It shows a minimalist setup using standard Proximal Policy Optimization (PPO) with https://x.com/rohanpaul_ai/status/1908776692140958153
“Nothing beats @augmentcode answering questions about large codebases. It’s a free extension (works in VSCode, JetBrains, and NeoVim), and has a community edition you can run for free forever. Try this experiment: 1. Download any large open-source project from GitHub 2. Augment https://x.com/svpino/status/1910683951485902912
“Deepseek just announced Inference-Time Scaling for Generalist Reward Modeling on Hugging Face show that SPCT significantly improves the quality and scalability of GRMs, outperforming existing methods and models in various RM benchmarks without severe biases, and could achieve https://x.com/_akhaliq/status/1908167564057849903
“Bytedance releases Seed-Thinking-v1.5, a 200B reasoning model with 20B active parameters that beats DeepSeek R1 across domains 🤯 Read on for a detailed breakdown👇 https://x.com/casper_hansen_/status/1910373327832498242
“NEW: SoTA OCR model – Apache 2.0 licensed based on Qwen 2.5 VL 🔥 https://x.com/reach_vb/status/1908232634943365478
The best open source OCR models https://getomni.ai/blog/benchmarking-open-source-models-for-ocr
“Announcing DeepSeek V3 Company Researcher 🔦 Get structured company data from the web using Firecrawl’s new /extract endpoint. Open-source, powered by DeepSeek V3 & @firecrawl_dev. https://x.com/ericciarla/status/1910361910136258752
“@ryanbijoy It’s built on top of a good base model: Deepseek-R1-Distilled-Qwen-14B an open-source RL framework: ByteDance’s verl, and now they open source their extension verl-pipeline. exciting time for open source.” / X https://x.com/Yuchenj_UW/status/1910008307202548074
Introducing Cogito Preview https://www.deepcogito.com/research/cogito-v1-preview
“@Ahmad_Al_Dahle Congrats on the release again! Quite excited about future llamas 🦙 Always in awe of your commitment to open science and weights! It always takes some time to iron out all edge cases etc 🤗” / X https://x.com/reach_vb/status/1909316136526832054
“1,000,000 pageviews on research papers on HF in March. It’s becoming the best place to find, promote & discuss research in AI! https://x.com/ClementDelangue/status/1908176702502527046
“Github 👨🔧: TTS Towards Human-Sounding Speech ——- → Leverages a Llama-3b LLM backbone for speech synthesis, showcasing emergent capabilities. → Produces highly natural speech output, focusing on realistic intonation, emotion, and rhythm. → Supports zero-shot voice https://x.com/rohanpaul_ai/status/1909126492971536685
“Skywork R1V just dropped on Hugging Face Pioneering Multimodal Reasoning with Chain-of-Thought https://x.com/_akhaliq/status/1909934004205175086
5/Apr/2025 – ASI checklist item #5, Llama 4 Behemoth 2T on ~30T tokens, 1X NEO AGI – YouTube https://www.youtube.com/watch?v=oipjJwRVW20&t=888s
“Your first look at what’s coming up for LlamaCon on April 29th! Mark will be sitting down with Microsoft Chairman and CEO @satyanadella to discuss the latest trends in AI for devs; and with @databricks Co-Founder and CEO, Ali Ghodsi on open source AI + advice for founders. https://x.com/AIatMeta/status/1910361356500685206
“We @MistralAI are hiring lots in France, UK, USA, Germany and Singapore 🇫🇷 🇬🇧 🇺🇸 🇩🇪 🇸🇬 We need passionate innovators like you to make it happen! Join us! 🏗️ AI Solutions Architect: Empower our customers to unlock the full potential of AI. You’ll guide them through adopting our https://x.com/sophiamyang/status/1909289524959572460
