In short: Nvidia CEO Jensen Huang warned on the Dwarkesh Podcast that DeepSeek optimising its AI models for Huawei’s Ascend chips instead of American hardware would be “a horrible outcome” for the United States, as the Chinese AI lab prepares to launch its V4 foundation model on Huawei’s Ascend 950PR processor. The migration from Nvidia’s CUDA to Huawei’s CANN framework threatens to break the software-hardware dependency underpinning American AI dominance, even as US lawmakers push to place DeepSeek on the entity list for export control.

Nvidia CEO Jensen Huang said on the Dwarkesh Podcast on Wednesday that if DeepSeek optimised its new AI models to run on Huawei chips rather than American hardware, it would be “a horrible outcome” for the United States. The warning frames the emerging partnership between China’s most capable AI lab and its most advanced chipmaker as a direct threat to the technological leverage that has underpinned American AI dominance for the past decade.

“If future AI models are optimised in a very different way than the American tech stack,” Huang said, and as “AI diffuses out into the rest of the world” with Chinese standards and technology, China “will become superior to” the US. The statement is notable because it comes from the CEO of the company that has benefited most from the current arrangement, in which virtually every frontier AI model in the world is trained on Nvidia GPUs using Nvidia’s CUDA software framework.

What DeepSeek is building

DeepSeek is preparing to launch V4, a multimodal foundation model expected later this month. The Information reported earlier in April that V4 would run on Huawei’s latest Ascend 950PR processor, while a separate Reuters report suggested the model had been trained on Nvidia’s Blackwell chips, which would constitute a violation of US export controls. The two claims are not necessarily contradictory: a model can be trained on one set of hardware and deployed for inference on another.

What makes the Huawei integration significant is the software migration behind it. DeepSeek has spent months rewriting its core code to work with Huawei’s CANN framework, moving away from the CUDA ecosystem that Nvidia has spent two decades building into the foundation of AI development. CUDA’s dominance has functioned as a second layer of American control over AI, beyond the chips themselves. Export restrictions can limit which Nvidia hardware reaches China, but as long as Chinese labs wrote their software for CUDA, they remained dependent on the Nvidia ecosystem even when using alternative processors. DeepSeek’s move to CANN breaks that dependency.

DeepSeek’s V3 model, launched in late 2024, was trained on 2,048 Nvidia H800 GPUs, a chip tailor-made for the Chinese market that was itself banned from sale to China in 2023. The company has already demonstrated that it can produce frontier-competitive models with fewer resources than its American rivals. Its R1 reasoning model matched or exceeded the performance of models that cost orders of magnitude more to train. V4 would extend that approach by proving the company can do it without American hardware at all.

The hardware gap and why it may not matter

On raw performance, Huawei’s chips are not competitive with Nvidia’s best. The Ascend 910C, the predecessor to the 950PR, delivers roughly 60% of the inference performance of Nvidia’s H100, a chip that is itself two generations behind Nvidia’s current best. American chips are approximately five times more powerful than their Chinese equivalents today, and that gap is projected to widen to 17 times by 2027. Huawei is targeting 750,000 AI chip shipments in 2026, but its total production represents only 3 to 5% of Nvidia’s aggregate computing power.

But Huang’s concern is not about the current performance gap. He said on the podcast that even if China had inferior chips, it could still catch up with the US in AI development given its “abundant energy” and “large pool of AI researchers.” The implication is that raw hardware performance is only one variable, and that software optimisation, researcher talent, and energy availability can compensate for silicon disadvantages. If V4 performs well on Ascend chips, it validates an alternative path for AI development that does not depend on Nvidia at any point in the supply chain.

The export control paradox

The situation exposes a tension at the centre of American chip export policy. Nvidia restarted production of the H200, a more powerful chip, for sale in China, as Huang confirmed in March. But China has been blocking H200 imports to protect Huawei’s domestic chip business, and Nvidia’s CFO has said the company has recorded no revenue from China H200 sales. The controls designed to limit China’s AI capabilities are instead accelerating the development of a Chinese alternative.

DeepSeek’s experience with its R2 model illustrates both the promise and the limits of the Huawei path. R2 was repeatedly delayed because of training failures on Huawei hardware. Chinese authorities had urged DeepSeek to train on domestic chips, but the company encountered stability issues that forced it to revert to Nvidia GPUs for training while using Huawei chips only for inference. The distinction matters: training is the most compute-intensive phase of AI development, and the fact that Huawei chips could not handle it reliably suggests the hardware gap is real. But inference, the phase where models serve users, is where commercial value is generated, and Huawei’s chips appear adequate for that purpose.

Meanwhile, US lawmakers are pushing to tighten restrictions further. On Thursday, lawmakers and experts accused China of buying “what they can” and stealing “what they cannot” in the AI industry, and called for the government to evaluate placing DeepSeek, Moonshot AI, and MiniMax on the entity list for export control.

What Huang is really warning about

Huang’s warning is ultimately about software-hardware co-design. Nvidia’s dominance rests not just on making the fastest chips but on CUDA’s position as the default development environment for AI. When researchers write code, they write it for CUDA. When startups build products, they build them on CUDA. When governments invest in AI infrastructure, they buy Nvidia GPUs because that is what the software requires. DeepSeek’s migration to CANN threatens to create a parallel ecosystem in which none of that applies.

The scale of Nvidia’s business makes the stakes concrete. The company’s market capitalisation exceeds $3 trillion. Its data centre revenue grew 93% year over year in its most recent quarter. Its chips power the training runs for virtually every major AI model outside China. If the most capable Chinese AI lab demonstrates that competitive models can be built without Nvidia, the argument for maintaining export controls weakens, the argument for buying Nvidia weakens, and the geopolitical assumptions that have shaped AI policy for the past three years come under pressure.

None of this means Huawei is about to overtake Nvidia. The performance gap is large and growing. The R2 training failures demonstrate that Chinese hardware is not yet ready for the most demanding AI workloads. But Huang is not warning about today. He is warning about a trajectory in which DeepSeek proves the concept, other labs follow, and the CUDA moat that has made Nvidia the most valuable company in the AI supply chain begins to erode.

The fact that the CEO of Nvidia is the one making this argument publicly suggests he believes the risk is no longer theoretical. DeepSeek’s V4 will be the first major test. If a multimodal foundation model runs competitively on Huawei silicon, the warning Huang issued on Wednesday will look less like corporate lobbying and more like the most consequential forecast in the AI chip war so far.

For the past year, early adopters of autonomous AI agents have been forced to play a murky game of chance: keep the agent in a useless sandbox or give it the keys to the kingdom and hope it doesn’t hallucinate a catastrophic “delete all” command.

To unlock the true utility of an agent—scheduling meetings, triaging emails, or managing cloud infrastructure—users have had to grant these models raw API keys and broad permissions, raising the risk of their systems being disrupted by an accidental agent mistake.

That tradeoff ends today. The creators of the open source sandboxed NanoClaw agent framework — now known under their new private startup named NanoCo — have announced a landmark partnership with Vercel and OneCLI to introduce a standardized, infrastructure-level approval system.

By integrating Vercel’s Chat SDK and OneCLI’s open source credentials vault, NanoClaw 2.0 ensures that no sensitive action occurs without explicit human consent, delivered natively through the messaging apps where users already live.

The specific use cases that stand to benefit most are those involving high-consequence “write” actions. That is, in DevOps, an agent could propose a cloud infrastructure change that only goes live once a senior engineer taps “Approve” in Slack.

For finance teams, an agent could prepare batch payments or invoice triaging, with the final disbursement requiring a human signature via a WhatsApp card.

Technology: security by isolation

The fundamental shift in NanoClaw 2.0 is the move away from “application-level” security to “infrastructure-level” enforcement. In traditional agent frameworks, the model itself is often responsible for asking for permission—a flow that Gavriel Cohen, co-founder of NanoCo, describes as inherently flawed.

“The agent could potentially be malicious or compromised,” Cohen noted in a recent interview. “If the agent is generating the UI for the approval request, it could trick you by swapping the ‘Accept’ and ‘Reject’ buttons.”

NanoClaw solves this by running agents in strictly isolated Docker or Apple Containers. The agent never sees a real API key; instead, it uses “placeholder” keys. When the agent attempts an outbound request, the request is intercepted by the OneCLI Rust Gateway. The gateway checks a set of user-defined policies (e.g., “Read-only access is okay, but sending an email requires approval”).

If the action is sensitive, the gateway pauses the request and triggers a notification to the user. Only after the user approves does the gateway inject the real, encrypted credential and allow the request to reach the service.

Product: bringing the ‘human’ into the loop

While security is the engine, Vercel’s Chat SDK is the dashboard. Integrating with different messaging platforms is notoriously difficult because every app—Slack, Teams, WhatsApp, Telegram—uses different APIs for interactive elements like buttons and cards.

By leveraging Vercel’s unified SDK, NanoClaw can now deploy to 15 different channels from a single TypeScript codebase. When an agent wants to perform a protected action, the user receives a rich interactive card on their phone. “The approval shows up as a rich, native card right inside Slack or WhatsApp or Teams, and the user taps once to approve or deny,” said Cohen. This “seamless UX” is what makes human-in-the-loop oversight practical rather than a productivity bottleneck.

The full list of 15 supported messaging apps/channels contains many favored by enterprise knowledge workers, including:

• Slack

• WhatsApp

• Telegram

• Microsoft Teams

• Discord

• Google Chat

• iMessage

• Facebook Messenger

• Instagram

• X (Twitter)

• GitHub

• Linear

• Matrix

• Email

• Webex

Background on NanoClaw

NanoClaw launched on January 31, 2026, as a minimalist and security-focused response to the “security nightmare” inherent in complex, non-sandboxed agent frameworks.

Created by Cohen, a former Wix.com engineer, and marketed by his brother Lazer, CEO of B2B tech public relations firm Concrete Media, the project was designed to solve the auditability crisis found in competing platforms like OpenClaw, which had grown to nearly 400,000 lines of code.

By contrast, NanoClaw condensed its core logic into roughly 500 lines of TypeScript—a size that, according to VentureBeat, allows the entire system to be audited by a human or a secondary AI in approximately eight minutes.

The platform’s primary technical defense is its use of operating system-level isolation. Every agent is placed inside an isolated Linux container—utilizing Apple Containers for high performance on macOS or Docker for Linux—to ensure that the AI only interacts with directories explicitly mounted by the user.

As detailed in VentureBeat’s reporting on the project’s infrastructure, this approach confines the “blast radius” of potential prompt injections strictly to the container and its specific communication channel.

In March 2026, NanoClaw further matured this security posture through an official partnership with the software container firm Docker to run agents inside “Docker Sandboxes”.

This integration utilizes MicroVM-based isolation to provide an enterprise-ready environment for agents that, by their nature, must mutate their environments by installing packages, modifying files, and launching processes—actions that typically break traditional container immutability assumptions.

Operationally, NanoClaw rejects the traditional “feature-rich” software model in favor of a “Skills over Features” philosophy. Instead of maintaining a bloated main branch with dozens of unused modules, the project encourages users to contribute “Skills”—modular instructions that teach a local AI assistant how to transform and customize the codebase for specific needs, such as adding Telegram or Gmail support.

This methodology, as described on NanoClaw’s website and in VentureBeat interviews, ensures that users only maintain the exact code required for their specific implementation.

Furthermore, the framework natively supports “Agent Swarms” via the Anthropic Agent SDK, allowing specialized agents to collaborate in parallel while maintaining isolated memory contexts for different business functions.

Licensing and open source strategy

NanoClaw remains firmly committed to the open source MIT License, encouraging users to fork the project and customize it for their own needs. This stands in stark contrast to “monolithic” frameworks.

NanoClaw’s codebase is remarkably lean, consisting of only 15 source files and roughly 3,900 lines of code, compared to the hundreds of thousands of lines found in competitors like OpenClaw.

The partnership also highlights the strength of the “Open Source Avengers” coalition.

By combining NanoClaw (agent orchestration), Vercel Chat SDK (UI/UX), and OneCLI (security/secrets), the project demonstrates that modular, open-source tools can outpace proprietary labs in building the application layer for AI.

Community reactions

As shown on the NanoClaw website, the project has amassed more than 27,400 stars on GitHub and maintains an active Discord community.

A core claim on the NanoClaw site is that the codebase is small enough to understand in “8 minutes,” a feature targeted at security-conscious users who want to audit their assistant.

In an interview, Cohen noted that iMessage support via Vercel’s Photon project addresses a common community hurdle: previously, users often had to maintain a separate Mac Mini to connect agents to an iMessage account.

The enterprise perspective: should you adopt?

For enterprises, NanoClaw 2.0 represents a shift from speculative experimentation to safe operationalization.

Historically, IT departments have blocked agent usage due to the “all-or-nothing” nature of credential access. By decoupling the agent from the secret, NanoClaw provides a middle ground that mirrors existing corporate security protocols—specifically the principle of least privilege.

Enterprises should consider this framework if they require high-auditability and have strict compliance needs regarding data exfiltration. According to Cohen, many businesses have not been ready to grant agents access to calendars or emails because of security concerns. This framework addresses that by ensuring the agent structurally cannot act without permission.

Enterprises stand to benefit specifically in use cases involving “high-stakes” actions. As illustrated in the OneCLI dashboard, a user can set a policy where an agent can read emails freely but must trigger a manual approval dialog to “delete” or “send” one.

Because NanoClaw runs as a single Node.js process with isolated containers , it allows enterprise security teams to verify that the gateway is the only path for outbound traffic. This architecture transforms the AI from an unmonitored operator into a supervised junior staffer, providing the productivity of autonomous agents without forgoing executive control.

Ultimately, NanoClaw is a recommendation for organizations that want the productivity of autonomous agents without the “black box” risk of traditional LLM wrappers. It turns the AI from a potentially rogue operator into a highly capable junior staffer who always asks for permission before hitting the “send” or “buy” button.

As AI-native setups become the standard, this partnership establishes the blueprint for how trust will be managed in the age of the autonomous workforce.

• Nuclear clocks promise accuracy far beyond existing atomic timekeeping systems
• Thorium 229 offers a rare pathway to practical nuclear time measurement
• Ultraviolet breakthrough reduces one of the hardest barriers in nuclear clock development

A new crystal developed by Chinese scientists has broken the world record for ultraviolet light conversion, bringing nuclear clock technology closer to reality.

The fluorinated borate compound pushes laser light to a wavelength of 145.2nm, beating the previous benchmark of 150nm set by a Chinese crystal from the 1990s.

Cerebras Systems, a startup building what CEO Andrew Feldman describes as “the fastest AI hardware for training and inference,” has filed to go public.

The company previously filed for an initial public offering in 2024, but that was delayed due to a federal review of an investment from Abu Dhabi-based G42 and was ultimately withdrawn. Cerebras raised a $1.1 billion Series G last year, followed by a $1 billion Series H in February at a $23 billion valuation, according to the Wall Street Journal.

In recent months, the company announced an agreement with Amazon Web Services to use Cerebras chips in Amazon data centers, as well as a deal with OpenAI reportedly worth more than $10 billion.

In a recent interview with the WSJ, Feldman boasted, “Obviously, [Nvidia] didn’t want to lose the fast inference business at OpenAI, and we took that from them.”

Cerebras brought in $510 million in revenue in 2025, according to the filing, with a net income of $237.8 million (excluding certain one-time items, it was a non-GAAP net loss of $75.7 million).

A company has not disclosed how much it hopes to raise in the IPO. A spokesperson said the offering is planned for mid-May.

Google just made one of Gemini’s most useful features available to everyone. The Notebooks feature, initially rolled out to paid AI subscribers earlier this month, is now available to all free users on the web. If you use Gemini regularly, this is a pretty big deal.

What is Gemini’s Notebooks feature and what can you do with it?

Think of Notebooks as a dedicated project workspace inside Gemini. Instead of starting fresh every time you open the app, you can store your conversations, files, and sources all in one place under a single topic. Gemini then uses everything in that notebook as context when you ask your next question.

The feature shows up as a new Notebooks section in Gemini’s side panel, right between Gems and Chats. Any conversation you have inside Gemini can be saved to a notebook using the three dots menu.

You can also set custom instructions to control the tone, format, and style of responses. If you prefer Gemini to answer without referencing your saved chats, there is also an option to turn off notebook memory entirely.

What makes this genuinely exciting is the NotebookLM integration. These are the same notebooks used in NotebookLM, Google’s standalone research tool. Since the two sync automatically, any source you add in one app instantly appears in the other. That means you can research something in Gemini and then use NotebookLM’s Video Overviews and Infographics features on the same material, without any manual transfers.

How many sources can free Gemini users add to a notebook?

Free users can add up to 50 sources per notebook. If you are on a paid plan, the limits scale up considerably: AI Plus subscribers get 100 sources, Pro users get 300, and Ultra subscribers can go up to 600. The feature currently supports Gemini’s full toolkit, including web search and other AI-powered functions.

For now, Notebooks is live on the web only. It has not yet reached mobile or Mac apps, though broader availability is expected in the coming weeks.

At a trendy venue near the San Francisco pier, Sam Altman’s verification project World celebrated its next evolution and rapid expansion of its ambitions.  And it’s starting with Tinder.

Tools for Humanity (TFH), the company behind the World project, announced Friday plans to integrate its verification tech into dating apps, event and concert ticketing systems, business organizations, email, and other arenas of public life.

“The world is getting close to very powerful AI, and this is doing a lot of wonderful things,” said Altman, speaking before a packed crowd at The Midway. “We are also heading to a world now where there’s going to be more stuff generated by AI than by humans,” he added. “I’m sure many of you [have had moments] where you’re like, ‘Am I interacting with an AI or a person, or how much of each, and how do I know?”

World (formerly Worldcoin) distinguishes itself from many of its ID verification peers by offering the ability to verify that a real, living human is using a digital service while still protecting that person’s anonymity. There is some complex cryptographic alchemy behind this (something called “zero-knowledge proof-based authentication”). The upshot: The company is creating what it calls “proof of human” tools, which are mechanisms that can verify human activity in a world rife with AI agents and bots.

Its chief tool for verification is a spherical digital reader called the Orb that scans a user’s eyes, converting their iris into a unique and anonymous cryptographic identifier (known as a verified World ID). This can then be used to access World’s services, although users can also access World’s app without one.

Altman kept his remarks brief on Friday (TFH’s co-founder and CEO, Alex Blania, was absent due to a last-minute hand surgery, Altman said). He then turned much of the presentation over to World’s chief product officer, Tiago Sada, and his team.

Sada explained that World was launching the newest version of its app (the last version was launched at an event in December), along with a plethora of new integrations for its technology.

World has been preparing, for some time, to deploy a verification service for dating apps — most notably, Tinder. Last year, Tinder launched a World ID pilot program in Japan. That pilot was apparently a success because World announced that Tinder would be launching its verification integration in global markets —including the U.S. The program integrates a World ID emblem into the profiles of users who have gone through its verification processes, thus authenticating them as a real person.

World is also courting the entertainment industry by launching a new feature called Concert Kit, where musical artists can reserve a certain number of concert tickets for World ID-verified humans. This is designed to ensure that fans are safe from scalpers who often use automated ticket-buying bots to scarf up seats. Concert Kit is compatible with major ticketing systems, including Ticketmaster and Eventbrite, and the company is promoting it via partnerships with 30 Seconds to Mars and Bruno Mars — both of whom plan to use it for their upcoming tours.

The event was full of many other announcements, including some aimed at businesses. A Zoom/World ID verification integration seeks to battle a supposed deepfake threat to business calls, and a Docusign partnership is designed to ensure signatures come from authentic users.

The company is also working on a number of features in anticipation of the Wild West of the agentic web, including one called “agent delegation,” in which a person can delegate their World ID to an agent to carry out online activities on their behalf. A partnership with authentication firm Okta has also created a system (currently in beta) that verifies that an agent is acting on behalf of a human. The system is set up so that a World ID can be tied to a specific agent and then, when the agent goes out into the web to operate on that person’s behalf, websites will know a verified person is behind the behavior, said Okta’s chief product officer, Gareth Davies, at the event.

So far, it’s been difficult for World to scale, due largely to the verification process itself. For much of the company’s history, to get its gold standard, you had to travel to one of its offices and have your eyeballs scanned by an Orb — a fairly inconvenient (not to mention weird) experience.

However, World has continually made moves to increase the ease and incentive structure for verification. In the past, it offered its crypto asset, Worldcoin, to some members who signed up and has distributed its Orbs into big retail chains so that users can verify themselves while they’re out shopping or getting a coffee. Now the company is announcing that it is significantly expanding its Orb saturation in New York, Los Angeles, and San Francisco. The company also promoted a service where interested users could have World bring an Orb to their location for remote verification.

In a conversation with TechCrunch, Sada also shared that World has attempted to solve the scaling problem by creating different tiers of verification. The highest tier is Orb verification, but below that, World has previously offered a mid-level tier, which uses an anonymized scan of an official government ID via the card’s NFC chip.

The company also introduced a low-level tier, or what Sada called “low friction”— meaning low effort, I guess, but also “low security” — which involves merely taking a selfie.

Selfie Check, which Sada’s team presented during the event, is designed to maintain user privacy.

“Selfie is private by design,” said Daniel Shorr, one of TFH’s executives, during the presentation. “That means that we maximize the local processing that’s happening on your device, on your phone, which means that your images are yours.”

Selfie verification obviously isn’t new, and fraudsters have long managed to spoof it. “Obviously, we do our best, and it’s like one of the best systems that you’ll see for this. But it has limits,” Sada told TechCrunch. Developers looking to integrate World’s services can choose from the three different verification tiers depending on the level of security that’s important to them, he noted.

Victrola and Third Man Records have officially pulled the trigger on their limited-edition collaboration for Record Store Day 2026, adding a hardware angle to a weekend we’ve already covered heavily from the music side including some of the most sought-after releases hitting bins today. This time, it’s not about what you’re chasing on vinyl, it’s what you’ll be spinning it on.

The release pairs the custom Victrola VPT 1520 TMR turntable with a matching set of VPS 400 TMR Tempo bookshelf speakers, both finished in Third Man’s signature yellow-and-black. The collection is available separately or as a bundle via Third Man’s official site and Victrola’s dedicated page, along with in-store availability at Third Man Records locations in Detroit, Nashville, and London.

The launch coincides with Record Store Day events, including a celebration at the label’s Detroit pressing plant.

“I’ve had the opportunity to visit Third Man many times, and if you haven’t been to one of their locations, you need to go,” said Scott Hagen, CEO of Victrola. “What Jack and his team have built is something truly magical,” Hagen continued. “They aren’t just painting things yellow and black—it’s as if they’re bringing inanimate objects to life, each one with its own character and soul. Maybe that’s why vinyl and vinyl culture fit so naturally within the Third Man world. It’s certainly why Victrola was incredibly honored when Third Man asked us to design and bring these new products to market together. I’m super proud of the outcome. Anyone who loves Third Man is going to need this new turntable and speakers in their life.”

Third Man Records x Victrola Wave VPT 1520 TMR  Turntable 

The Third Man Records x Victrola Wave VPT 1520 TMR turntable features an MDF plinth, adjustable counterweight, removable headshell, and high-resolution Bluetooth with Auracast support. It’s finished in a custom black-and-yellow color scheme with the Third Man globe logo prominently integrated into the design.

• Drive Method: Belt drive
• Speeds: 33 ⅓ and 45 RPM
• Cartridge: Ortofon OM5E
• Bluetooth Version: 5.4
• Bluetooth Codecs: aptX Adaptive, aptX HD, SBC, LC3 (Auracast supported)
• Profiles: A2DP, AVRCP
• Outputs:
  • RCA (built-in preamp: 200–280 mV)
  • Phono (2.5 mV ±3 dB)
• Power Input: AC 100–240V, 50/60Hz
• Dimensions: 16.93″ W x 14.84″ L x 4.72″ H
• Weight: 13 lbs (with cover)
• Included: Dust cover, platter, silicone slipmat, 45 RPM adapter, 6′ RCA cable, manual

Third Man Records x Victrola VPS 400 TMR Wireless Powered Speakers

The VPS 400 TMR Tempo powered bookshelf speakers round out the system with flexible wired and wireless connectivity, including Bluetooth and Auracast support for multi-room playback with up to 10 speakers.

• Inputs: Bluetooth, Auracast Broadcast Audio, 3.5mm AUX, RCA, USB-C (PC/flash drive), Optical (Toslink)
• Outputs: Auracast Broadcast Audio, Subwoofer out (with hi-pass “Bass Filter”)
• Dimensions (Right/Primary): 5.91″ W x 7.76″ D x 8.86″ H (150 x 197 x 225 mm)
• Dimensions (Left/Secondary): 5.91″ W x 8.07″ D x 8.86″ H (150 x 205 x 225 mm)
• Weight (Pair): 9.47 lbs (4.30 kg)
• Included: Right and left speakers, power cord (1.5m), speaker interconnect cable (4m), RCA cable (1.5m), 3.5mm cable (1.5m), instruction manual

Third Man Records x Victrola Vinyl Collection

To round out the collaboration, Victrola has curated a capsule collection of Third Man Records titles available at Victrola.com/thirdmanrecords, pairing the hardware launch with some of the label’s most recognizable releases.

• Featured Titles:
  • Elephant – The White Stripes
  • Blunderbuss – Jack White
  • Broken Boy Soldiers – The Raconteurs

The Bottom Line 

The collaboration between Victrola and Third Man Records is a straightforward, practical play tied to Record Store Day 2026. Instead of focusing only on records, it connects the purchase of vinyl with a ready-to-use playback system.

What stands out is the combination of a belt-drive turntable with a known cartridge and powered speakers that include both wired inputs and modern wireless features like Bluetooth and Auracast. That flexibility allows users to play records, stream from a phone, or send audio to other compatible speakers without adding more components.

At $499.99 for the turntable, $249.99 for the speakers, or $649.98 for the bundle, this is aimed at newer vinyl buyers or casual listeners who want a complete system without building one piece by piece. It lowers the barrier to entry while offering more functionality than entry-level all-in-one options.

It’s not intended for more advanced systems or users looking to upgrade individual components over time, but for its target audience, the value is in simplicity and convenience rather than maximum performance.

Price & Availability

• VPT 1520 TMR Turntable – $499.99 
• VPS 400 TMR Powered Wireless Speakers – $249.99
• Turntable/Speaker bundle – $649.98

Tip: The Victrola Wave turntable (regular edition) is available at Amazon, as well as the Victrola Tempo speakers, which are the same models without yellow branding.

Related Reading: