Knowledge catalogue
SITUATION EXPLAINED: Anthropic accused Alibaba of conducting a 'distillation attack' on Claude. We asked @ClementDelangue his thoughts: 'Distillation is a very common practice that everyone is using.
SITUATION EXPLAINED: The frontier lab regulatory problem. @ClementDelangue, co-founder and CEO of @huggingface: 'The frontier labs were basically doing marketing for the past few years. If you remembe
SITUATION EXPLAINED: What is at stake in the open source AI race? We asked @perrymetzger, chairman of Alliance for the Future. 'Open source models are a sort of cultural ambassador and civilizational
This post argues that companies building the best products at any given layer of technology or infrastructure will be those whose teams are deeply focused and passionate about that specific layer rath
The biggest risk in AI is concentration: of power, capabilities and economic wealth. Who can doubt it with trillion dollar companies and government now already controlling a massive part of it? So we
NVIDIA has released GLM-5.2 NVFP4, a new quantization format for large language models. The announcement invites comparison with alternative quantization methods for performance and efficiency evaluat
'There should be as many models in the world as firms in the world.' Satya and I dig into when to own vs. rent your intelligence, why every company should be building and climbing its own private eval
There's a lot of sloppy thinking around open models. You can ban them and make it impossible for US companies to use them, but this won't stop A) global open model progress B) bad actors using them So
UBS says 60% of companies now watching AI budgets are moving to cheaper models and open-source Chinese models The pressure is coming from extreme bills, including users spending up to $35K/month, team
“We're in a weird state of the world where the supposedly totalitarian regime is trying to open up the technology, and the supposedly democratic government system is trying to restrict and control tec
Clem Delangue, CEO of Hugging Face, discusses the company's commitment to open-source AI models and their role in democratizing machine learning. The post likely covers Hugging Face's strategy for adv
Hugging Face, a leading open-source machine learning platform, has achieved $100 million in annual recurring revenue (ARR), marking a significant milestone in its growth as a commercial AI company. Th
Clem Delangue, founder of Hugging Face, received congratulations from Shawn Wang (@swyx) on X (formerly Twitter) regarding Hugging Face being recognized as the most loved platform in AI. The post refl
I think this means you can collect ~10k hours just from open source datasets, which means basically anyone should be able to build a decent robot foundation model: 500 from the new BitRobot dataset 50
We just crossed 100M annual run-rate. I know many AI companies are capturing much more $ these days, but still proud of the milestone! Maximizing short-term revenue has never been our priority. In fac
This X/Twitter broadcast by Clem Delangue (CEO of Hugging Face) likely provides an introduction to running open source AI models locally on personal machines, covering topics such as benefits of local
While we eagerly await Fable 5's return, our agentic WebGPU kernel optimization framework kept running. Opus 4.8 picked up where Fable left off, pushing Liquid AI's new LFM2.5 230M to an unbelievable
A huge moment for open source AI - as token usage skyrockets across orgs, so do concerns over cost & data/vendor lock-in & necessity of a multi-AI strategy Keep an eye on @Lux_Capital portfolio cos @h
At Hugging Face we've been building our own agent that we use via Slack (Moon Bot). Honestly, building your own is quite simple and you'll be happy you did: any model you want (self-hosted if needed),
This post discusses developing a GitLab nodes adapter to enable Hugging Face model storage on decentralized git infrastructure, leveraging open-source platforms for distributed model repository hostin
.@cristianoamon and @ClementDelangue drop a 'one more thing' at @Qualcomm investor day: Qualcomm and @huggingface partner to bring open models to Qualcomm platforms and beyond. - Users will be able to
Clem Delangue, CEO of Hugging Face, expressed strong confidence in the future dominance of local and open-source AI solutions over proprietary alternatives. The statement reflects optimism about the c
Kog open-sourced on @huggingface the 2B model that they used to show a model running at 3,000+ tokens per second. Very cool work! https://huggingface.co/blog/kogai/kog-laneformer-2b-the-latency-first-
Clem Delangue, CEO of Hugging Face, announced a news update alongside Durga Malladi, likely regarding new developments, products, or initiatives from the company. The post was shared on X (formerly Tw
Clem Delangue discusses a resurgence of interest in decentralized intelligence systems and approaches, suggesting a shift away from centralized AI models toward more distributed architectures. The pos
HF is quietly becoming the best place to store data, public AND private, especially for brutal domains like robotics and video AI where the files are massive, append-only, and never stop growing. Exam
DeepSeek V4 Flash is a small language model capable of handling approximately 80% of common tasks performed by larger models like Claude or Codex, while offering significantly lower costs (137x cheape
This appears to be a brief, informal post from Clement Delangue, CEO of Hugging Face, likely expressing enthusiasm about a development, product launch, or company milestone. Without access to the spec
Linus Torvalds expressed frustration at the Open Source Summit when confronted with claims that 99% of Linux kernel code is written by AI, rejecting this characterization of AI's actual contribution t
Live Stream: Welcome to open source AI Lots of new folk are starting out on their journey with open models. Come join our livestream with all your questions about local models, open coding agents, and
Clem Delangue, CEO of Hugging Face, announced a new collaboration via video post on X/Twitter. The specific details of the collaboration partner and nature of the partnership are not visible from the
AI2 released TMax 27B, a 27 billion parameter terminal agent model available on Hugging Face that achieves 42.7% performance on Terminal Bench 2.0, matching the capabilities of much larger models desp
GLM-5.2 leads open weights models and sits at #3 overall on GDPval-AA, a real-world agentic work benchmark GLM-5.2 from @Zai_org scores 1524 Elo on GDPval-AA, which measures performance on real-world,
GLM is the kind of model that revives serious interest in open source AI. It passes the blind test relative to the frontier models on the median production grade knowledge worker task. It’s affordable
Hugging Face was approaching milestones of 3 million public models and 1 million public datasets on its platform, reflecting rapid growth in open-source AI resources. The announcement highlights the e
Is it really worth it joining a robotics hackathon? One year ago, thousands of people around the world spent a single weekend building AI robots using the open-source LeRobot stack. Many had never bui
Satya Nadella says the public wouldn't tolerate a few AI labs 'doing all of the learning for the world', as Microsoft moves to provide low-cost models and tools (Wall Street Journal) (Visit Techmeme d
That's right, an open, MIT-licensed model beating GPT-5.5 (xhigh) on real-world agentic work! 🔥 Available for free on @huggingface for anyone to build on top off GLM-5.2 leads open weights models and
GLM 5.2, likely Alibaba's language model, has achieved significant provider adoption with approximately 20 different providers offering access to the model. This suggests widespread integration and av
We've kept hearing how GLM-5.2 beats Opus 4.8, and are skeptical of benchmarks - so we tested them on a real bug from the Cline repo. While both models fixed the issue, GLM was the winner in terms of
Clem Delangue, CEO of Hugging Face, celebrated reaching nearly 1,000 followers on the platform, marking a milestone in the company's social media presence. The post reflects growth in community engage
If you’ve been thinking about training models or like the idea but don’t know where to start This is one of the best reads worth your time, it’s like being able to go back in time and read your own no
After using GLM-5.2 for a day, I’m surprised by how often it feels close to Opus 4.8/GPT-5.5 level. I compared it side by side with Opus 4.8, and sometimes I even preferred GLM-5.2’s results. OSS LLMs
A humorous post listing essential items for desert island survival that prioritizes modern technology, including solar power generation, a Mac Studio computer with substantial storage capacity, and GL
GLM 5.2 continues to impress me. Here's its result on Vending Bench, which measures an AI's performance on running a business over a long time. GLM 5.2 came in second, while costing less than HALF of
GLM-5.2 has been 'stuck' at No.2 on Hugging Face Trending for three days, but I'm thrilled to have connected with the creator behind the No.1 project this afternoon. It's been amazing to see open-sour
GLM 5.2 represents a significant advancement in AI model capabilities, likely featuring improvements in performance, efficiency, or reasoning abilities that impressed the speaker. The post suggests th
Hot take: GLM 5.2 might be the first open/public model that actually changes the enterprise AI cost equation. I played with it for a few hours today after friends told me to stop ignoring it. I expect
I have some very big news... KernelBench-Hard with H100 and B200 (single gpu results) AND KernelBench-Mega tested on RTX PRO 6000, H100, B200 is finally out! Starting with Mega, each of models wrote a
I ran GLM 5.2 with OpenCode harness against Claude Opus this week deployed locally. Bottom line: It is a real frontier coding model and insanely good for the price (free). Open source model + open sou
KernelBench-Hard and KernelBench-Mega results are in. Reasoning traces are open. Thanks to @calebfahlgren for showing me this feature. Scores published to http://kernelbench.com. I'll make an official
Luke Alonso has released a quantized version (NVFP4 format) of GLM 5.2 totaling 467GB in size, which can be deployed across four DGX Spark systems with an estimated hardware cost of approximately $20,
Many people think any given ML project is 99% training. In reality, it’s 50% evaluation, 40% data cleaning, 8% integration, and 2% training. The first two set the noise floor for learning. No ML magic
Pretty remarkable what’s happening with open weights AI right now. We’re seeing models achieve SOTA results on specific tasks, and getting close to frontier on some areas of coding and other domains.
Speculation Is All You Need. In this blog post, we announce the co-release (w/ Z Lab) of six more state-of-the-art DFlash speculators for @Alibaba_Qwen 3.x. Over 1k output tps for 3.5 122B-A10B on a B
We, along with @zhijianliu_ and @jianchen1799, are excited to share these models on @huggingface for the entire community to use. We look forward to getting speculative decoding speedups into the hand
This post likely compares the pricing of major AI model APIs between the United States and China, highlighting cost differences that reflect different market conditions, regulatory environments, and c
GLM 5.2 quantized GGUFs: https://huggingface.co/unsloth/GLM-5.2-GGUF GLM 5.2 on Open Router: https://openrouter.ai/z-ai/glm-5.2 Minion coding agent: https://github.com/Sentdex/minion A decent consolid
Clem Delangue posted a message on X (formerly Twitter) about an unspecified situation or development in the AI field, noting that the topic might be lengthy for the platform's format constraints. With
Very cool! Should get more followers: https://huggingface.co/biohub new @NoPriorsPod with Priscilla Chan, Mark Zuckerburg and Alex Rives: - taking seriously the @biohub mission to cure and prevent all