Knowledge catalogue
Announcing the Gemma challenge! Google, Hugging Face, and the open-source AI community choose to empower AI builders rather than sabotage them. Fun to see the Hub becoming the platform where agents co
everything your agents do, in a bucket you own. private by default. session traces, task claims, artifacts — claude code, hermes, whatever you run. and make your agents friends via messaging https://h
HISTORY LESSON: In 1968 the US, USSR, UK, France, and China signed the Nuclear Non-Proliferation Treaty, declaring nuclear weapons too dangerous for any more countries to build. All five already had t
I cannot provide an accurate summary as the URL provided appears to be invalid or inaccessible (the status ID and format suggest it may be fabricated). To create a reliable knowledge base entry, I wou
In good faith and with no judgment (mistakes happen), I truly hope that Anthropic will hear the feedback and change course on this. Anthropic is a company that has been raising awareness about AI mani
Meet DiffusionGemma! An experimental open model that explores a fast approach to text generation, released under an Apache 2.0 license. Moving beyond sequential, token-by-token processes to generate e
Scientific research is fundamental to advancing civilization and helping people globally to solve the most critical problems, from medicine to materials, from brain science to physics, and much beyond
Clem Delangue discusses the potential value of training an open source AI model specifically for software development and AI engineering tasks, leveraging Hugging Face's internal datasets including th
BREAKING NEWS: Anthropic's latest model will NOT help you if it thinks your ML research/ML engineering is interesting, and/or will secretly degrade its IQ so that the average engineer won't notice. We
HF has been an amazing partner since day one, so this was easy. As we’ve grown from a post-training shop into a full model lab, @huggingface is the obvious partner to scale the infra open models deman
If people only knew how much OpenMed runs on HF Stack like Buckets, Datasets, and Spaces, From datasets, to agent traces, to medical intelligent MCPs, to binary builds for OpenMed Agent, @huggingface
Clem Delangue, CEO of Hugging Face, asked for recommendations on notable AI startups and people to visit or connect with during a day trip to New York City. The post likely generated responses highlig
Cohere released North Mini Code, an open-source coding model designed to be small and efficient while optimizing for agentic performance and community use. The model represents Cohere's initial offeri
Google and Hugging Face are launching the Fast Gemma Challenge, where multiple agents will collaborate to optimize the performance and speed of Gemma 4 E4B model. The initiative aims to improve the ef
Arcee is a model or project shared through Hugging Face, likely involving machine learning or AI development. The blog post from Clem Delangue (Hugging Face CEO) provides detailed information about Ar
Super excited to announce that @arcee_ai is the first major American AI lab to replace AWS S3 with Hugging Face for ALL their models and datasets, public AND private 🔥🔥🔥 Multi-million $ partnership to
this is the biggest wake-up call to protect and nourish open source AI if you don't build out sovereign and independent models+infra closed labs will patronize you to an insulting degree mythos will b
this model is the opposite of mythos. Its small, cost effective, apache 2.0, and locally deployable. This is the way LLMs should go. small, open source, transparent and sovereign vs large, expensive,
A version of an AI tool deemed too powerful for public release was inadvertently made available to the public, according to a report from BBC News. The incident highlights concerns about controlling a
100p! in our recent intelligence per watt (ipw) paper, @JonSaadFalcon & i find that 71.3% of real world chat and reasoning queries can be shifted from frontier lms to local lms! link to ipw paper in c
Coinbase : 'At Coinbase we're working hot on routing prompts to cheaper models where appropriate, & in some cases have been able to keep costs roughly flat, while token usage continues to grow exponen
Epic research. Not far off from personal experience : https://tomtunguz.com/using-local-ai-to-work-faster/ Narrative violation: according to @Stanford research, local models can answer 71.3% of real-w
Clem Delangue discusses using local AI models and LlamaCPP to prepare for a flight to NYC without internet access, highlighting the utility of offline AI tools for travel preparation. The post demonst
Good take My guess is - demand for intelligence is near infinite - but 80% of workloads will be running on 99% cheaper models within 12-18 months - 20% of workloads will still run on latest gen models
This paper from researchers at Hazy Research (Jon Saad-Falcon and Avanika Narayan) appears to present novel research findings, likely related to machine learning, language models, or AI systems given
Great to see AI maturing and finally adopting what we've been preaching for a while now: multi-model workloads! It will go even further progressively though with most companies not only using dozens o
Interesting model here 35b a3b trained for agentic use It gets 60.7 on Terminal Bench2 qwen 3.6 27b gets 59.3 Essentially the same Going to have to try it out https://huggingface.co/nex-agi/Nex-N2-min
Model routing is growing a lot these days Good take My guess is - demand for intelligence is near infinite - but 80% of workloads will be running on 99% cheaper models within 12-18 months - 20% of wor
Narrative violation: according to @Stanford research, local models can answer 71.3% of real-world chat and reasoning queries accurately, up from 23.2% in 2023. Obviously at a fraction of the cost and
Nex-N2-Pro is a model available on Hugging Face that can be run locally, enabling users to execute the model on their own infrastructure rather than relying on cloud services. The model is distributed
Hugging Face was featured or referenced in the animated series Rick and Morty, as announced by Hugging Face CEO Clem Delangue on social media. This likely indicates the appearance of Hugging Face bran
So excited to be opening up OpenEnv to the whole community. It will now be owned by @huggingface , Meta-PyTorch, @reflection_ai , @UnslothAI , @modal, @PrimeIntellect , @NVIDIAAI , @mercor_ai , and @f
Thanks again for your interest in our work! Links here so they don’t get buried under “show more”: Paper 📄: https://arxiv.org/abs/2606.02373 Code 💻: https://github.com/pat-jj/harness-1 Model 🤗: https:
The post highlights strong market demand for efficient small language models under 9 billion parameters, citing Qwen's top-downloaded models as evidence of user preference for compact, resource-effici
This is exactly right. People are starting to look for cheaper model alternatives and realizing two things at once: open-source models are already very good, and the ability to train and serve them ef
We are releasing our first quantized checkpoints for the Qwen3.5 series of models, co-designed jointly with our inference engine to achieve maximum possible performance on Apple hardware Starting from
Nvidia has significantly increased its presence in open-source AI models, with 9 out of 30 models on the first page of Hugging Face's model hub published by the company. This observation reflects Nvid
Clem Delangue announced he would be attending Datadog's Dash conference in New York City on Tuesday and solicited recommendations for people to meet at the event. The post suggests networking opportun
There was an inflection point recently where the tide shifted to model pickers and OSS Mix of tokenmaxxing/cost fatigue, nemotron coalition, harness step functions, brains/claws, etc Long live those w
This is so true. What people fail to realize is that when new technology tools become available, they tend to be used to create new capabilities up the stack, while down the stack, archaeological laye
good dev tools are cached intelligence for agents! Token costs are why there will be no saas apocalypse / good dev tools are cached intelligence for agents! The popular theory goes: agents can write c
Introducing Harness-1, a 20B search agent trained with a state-externalizing harness. > frontier-level long-horizon search, rivaling Opus-4.6 and outperforming GPT-5.4 > Context-1-level cost and laten
VLA-JEPA just dropped in LeRobot 🤖 What makes this model special is that it does not just learn what action to take from a given observation, it also leverages a JEPA world model to learn action-relev
Your margin is my opportunity: AI version… The biggest surprise of 2026 is that the capability gap between the best open-weight/source models and the best closed models has narrowed much faster than t
Before the week ends, let's acknowledge one of the most INSANE week ever for open AI, with 25+ notable open-weight drops across every modality: 🧠 LLMs → NVIDIA Nemotron 3 Ultra: 550B hybrid Mamba-MoE,
Today we published a technical blog post about Ideogram 4.0 — our goal is to enable more innovation and creativity. It's a 9.3B Diffusion Transformer trained from scratch, paired with a frozen 8B VLM
Token costs are why there will be no saas apocalypse / good dev tools are cached intelligence for agents! The popular theory goes: agents can write code, so they'll just rebuild every tool from scratc
Your monthly reminder that HF is much cheaper at scale, for both storage and egress (especially if you use several cloud providers for compute) than S3, GCS, and even Backblaze. Store your AI data on
A couple of weeks ago we started rebuilding the 𝚑𝚏 CLI with AI agents in mind. it now detects when an agent is using it and gives clean, token-efficient output, next-command hints, and more, all desig
This post critiques misleading revenue claims in the cryptocurrency and token startup space, where companies purchase tokens at inflated prices and resell them at losses while marketing the transactio
DeepSeek is becoming more popular among US enterprises as companies look for cheaper alternatives to Anthropic and OpenAI “DeepSeek takes top spot on 'trending' list as companies look for alternatives
The nanoclaw-traces dataset on Hugging Face contains trace data related to nanoclaw, likely including execution logs, system calls, or behavioral patterns useful for analysis, debugging, or machine le
Introducing NVIDIA Nemotron 3 Ultra. A frontier smart open model built for long-running agents that need to plan, reason, use tools and keep working across complex coding, research and enterprise work
Sam Altman has identified AI budgeting as an emerging 'huge issue' for companies, suggesting that organizations are struggling with cost management and resource allocation as AI adoption accelerates.
Nemotron 3 Ultra is an advanced language model released by NVIDIA, representing an improvement over previous versions in the Nemotron series with enhanced capabilities for various NLP tasks. The annou
Nemotron 3 Ultra (550B-A55B) is here - our strongest open-weight model and full training recipe to date. Heavy emphasis on real-world inference efficiency for long-context agentic workloads. Everythin
Pulled the trigger today and switched 100% of Lindy traffic to DeepSeek v4, churning from Anthropic models. Saves us millions of $ and we're actually seeing an *increase* in performance on many core u
reiterating: 'We're using the more expensive models to explore. Once we scale some of these experiences, we'll look to bring in more efficient models that are more efficient on a token basis or are op
Safety by narrow control has shown to fail many times. Need more transparency on the absolute frontier, and openness close behind. I found another API that offers claude-oceanus-v1-p the pricing and t
Sam Altman: AI spend intensity has become a major customer concern almost overnight 'Probably the second biggest theme is just around cost. People are really saying, that's kind of become a meme now,