NVIDIA

Reuters reports Nvidia is in talks to anchor Anthropic's IPO with up to $10 billion. Anthropic aims to raise $100 billion at a ~$2 trillion valuation, which would make it the largest IPO ever. The deal isn't final and neither company has commented. Nvidia had already announced a $10 billion investment plan last November; this would fold that commitment into the IPO. Anthropic's annualized revenue run rate topped $65 billion by end of July 2026, up from ~$9 billion at end of 2025. The company is simultaneously deepening ties with AWS, Google TPUs, and its own custom chip efforts—adding Nvidia as an anchor locks in a key compute supplier and boosts confidence in the mega-listing.

Reuters says Nvidia is discussing an anchor investment of up to $10 billion in Anthropic's IPO. Anthropic is the maker of Claude. The move would tie Nvidia even tighter to a top AI lab that buys its chips. Talks are ongoing and the amount isn't final; both companies declined to comment. IPO-stage discussions can shift, but the $10B figure signals Nvidia wants more than a supplier relationship.

At Goldman Sachs' Communacopia conference, Jensen Huang said Nvidia's revenue will grow another 70% next year. His argument: AI compute demand is far from peaking as enterprises shift from training to large-scale inference, and Nvidia's GPU plus networking stack sits at every layer from cloud to edge. He also pushed back on 'circular deal' concerns—Nvidia invests in AI startups that then buy its chips—insisting each investment has standalone return logic. The article provides qualitative claims but no financial model or order data to back the 70% figure.

Edge AI actually covers three separate things: decades-old embedded narrow tasks, PC and phone makers riding hardware refresh cycles, and the recent push for on-device large models. The giants making real money—Apple, Qualcomm, Nvidia, MediaTek—never call themselves edge AI companies; on-device intelligence is just a routine chip component. Independent edge startups struggle: Hailo's valuation dropped from $1.2B to under $500M before Microchip acquired it, and Google Coral's code repo is now archived read-only. Consumer reception is cold—73% of iPhone and 87% of Samsung users see little value in AI features, and Microsoft dropped its NPU-exclusive strategy at Build 2026. The real profits are in industrial settings: Phonak hearing aids run neural denoising locally with a 10dB SNR boost, and Roborock shipped 5.8M units in 2025 with all visual inference on-device. After cloud API prices dropped ~99.7% in three years, edge's cost advantage has narrowed; the remaining hard reasons are latency, offline use, data locality, and compliance.

Nathan Lambert argues HuggingFace's ability to shape AI discourse is worth roughly $10B a year to Nvidia. He says Nvidia is a better buyer than the big three cloud providers, and HuggingFace should stop acting like a profit center and go after the next 100 million AI developers. Lambert previously worked at HuggingFace and predicted this acquisition last year. The post is an RSS snippet; it doesn't spell out deal terms or a timeline.

Nvidia's latest filing shows $99B in equity investments as of July 26—$48B in public stocks, $48B in private holdings. The portfolio was $7B a year ago and $2.2B two years ago, a 45x jump. CFO Colette Kress said on the earnings call that frontier AI labs are compute-constrained, so Nvidia 'needs to help turn this flywheel' and has invested nearly $50B in those labs. Disclosed positions include $30B in Intel, $21B in SpaceX, and $2–5B each in CoreWeave, Coherent, Synopsys, and Nokia. Michael Burry and Mark Cuban both flagged the model as overextended and risky.

OpenAI reported GPT-6 Astra at 98.6% on ARC AGI-3, but used a proprietary harness instead of the standard one. Nvidia already hit 100% with its AVO harness, and earlier systems like Arc-Skill and VISTA also neared perfect scores. Under the standard harness, Astra drops to 66%. That's still solid, but it's not AGI. The post doesn't spell out what OpenAI's custom harness changed, so I'd discount the 98.6% figure for now.

NVIDIA is acquiring Hugging Face, announced by Jensen Huang himself. He says the deal will strengthen open models in security, innovation, and sovereign AI, letting developers, startups, universities, and nations build and customize their own models. The post is a single-paragraph statement with no deal price, timeline, or integration details. Peter Steinberger retweeted calling it a perfect match—I'd hold off until we see actual terms.

NVIDIA announced it will acquire open-source AI platform Hugging Face for $12.93 billion. Jensen Huang explained in a blog post that Hugging Face hosts over 18 million developers, 3 million models, and 500,000 datasets. He pledged the platform will remain open, supporting open-weight models, multi-cloud, and multi-accelerator environments, and will not become a closed entry point for NVIDIA hardware. NVIDIA is already the platform's largest contributor with 500+ models and 250+ open datasets.

NVIDIA is acquiring Hugging Face. Jensen Huang says open models improve security, speed up innovation, and let developers, universities, and nations build their own AI. The post doesn't disclose price, timeline, or deal structure—only the announcement and a one-line statement are public so far.

NVIDIA is acquiring Hugging Face. Jensen Huang says open-source models speed up innovation and let developers, startups, and nations customize AI. Sundar Pichai reposted congratulations on X, saying it strengthens the open-source ecosystem. The post is one sentence — no price, timeline, or deal structure disclosed.

Nvidia confirmed it acquired Hugging Face for $12.93 billion. The platform hosts 3 million models, 1 million apps, and 500,000 datasets, used by over 18 million developers. CEO Jensen Huang said Hugging Face will stay open, with no requirement to use Nvidia compute. Nvidia has released 500+ models and 250 open datasets on the platform. Owning an open ecosystem helps Nvidia optimize for its chips and sell unused capacity.

Nvidia agreed to acquire Hugging Face for $12.93 billion, bringing the largest open-source model hosting community under the chip giant's roof. Founded in 2016, Hugging Face is often called the 'GitHub for AI'—developers share models, datasets, and tools there. Nvidia says it will scale the platform, strengthen infrastructure, and expand AI access. The post doesn't disclose the deal timeline or regulatory approvals.

Thomas Wolf posted on X that NVIDIA is acquiring Hugging Face for roughly $12.93 billion, with no changes for users that day. Wolf said the team will keep the Hub an open, independent, compute-agnostic platform and use NVIDIA's resources to push open-source AI. The post is a single-paragraph statement; it doesn't disclose deal structure, regulatory approvals, or integration timeline.

Bloomberg reports Nvidia is close to buying Hugging Face for about $12.9B, with the total deal potentially reaching $14B. That's 2.9x its 2023 valuation and roughly 86x annualized revenue of $150M. Nvidia also discussed a $1B employee retention package. No final agreement yet, and details could still shift.

Bloomberg reports Nvidia is close to acquiring AI model and dataset platform Hugging Face for roughly $14 billion, with a deal possible this week. The article body is behind a paywall, so deal terms, regulatory approvals, and integration plans are not disclosed.

Nvidia agreed to buy open-source model platform Hugging Face for $12.9B, its largest acquisition ever. Hugging Face's annual recurring revenue is about $150M, putting the deal at 86x ARR. Nvidia is buying the default entry point for global developers and the demand signals that come with it. Over the past two years, Nvidia and Microsoft repeatedly dodged antitrust reviews by licensing tech and hiring teams, but Hugging Face's core asset—13M users and platform traffic—can't be moved that way. A full equity purchase triggers mandatory review. The post notes that losing neutrality could cost the 41% of downloads coming from Chinese open-source models, eroding the trust that underpins the valuation.

Hugging Face's biannual report covers Jan–Aug 2026. Chinese labs released the largest open models almost every month, ranging from 754B to 2.78T parameters, while US labs mostly stayed under 130B except for NVIDIA's Nemotron 3 Ultra (561B) and Thinking Machines Lab's Inkling. Attention doesn't equal adoption: 85.6% of models have under 200 lifetime downloads, and 1.5% of repos account for 99.2% of downloads. Qwen is now the community's go-to base model, small models remain the practical layer, and agents are emerging as the new user of models.

Anthropic signed a $35 billion cloud deal with GPU cloud provider Lambda, locking in Nvidia-powered compute for training and inference. The article body is blocked by Bloomberg's bot-detection page, so contract duration, payment terms, and specific chip models aren't disclosed. What the headline confirms: the deal is $35 billion, and Lambda is Nvidia-backed. A commitment this size signals Anthropic is securing multi-year compute supply ahead of demand—I'd wait for more terms before judging the real cost structure.

Nvidia is investing $3.5B in MediaTek. In return, MediaTek will use Nvidia tech to design custom AI chips for hyperscalers and AI companies, chips that plug directly into Nvidia-based data centers. The move comes as Amazon, Google, Microsoft, OpenAI, and Anthropic all build their own AI silicon. The post doesn't disclose the equity stake or delivery timeline.