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Tenstorrent announced on December 2, 2024, that it had closed more than $693 million in Series D funding at a $2 billion pre-money valuation. Samsung Securities and AFW Partners led the round; Bezos Expeditions was one of the participating investors. The often-repeated “$700 million” figure is rounded, and “Samsung” here does not establish a direct investment by Samsung Electronics.
What the funding announcement actually said
Tenstorrent’s official announcement reported a Series D round of more than $693 million, commonly rounded to $700 million in secondary coverage. The company said the round was led by Samsung Securities and AFW Partners at a $2 billion pre-money valuation. Adding the announced financing to that pre-money figure implies an approximate $2.7 billion post-money valuation, although the company did not describe that as a separate valuation.
Named participants included Bezos Expeditions, XTX Markets, Corner Capital, Protagonist, MESH, Export Development Canada, Healthcare of Ontario Pension Plan, LG Technology Ventures, Hyundai Motor Group, Fidelity Management & Research Company, Innovation Engine and Baillie Gifford, along with other investors. Tenstorrent’s funding announcement is the primary source for the investor list and terms.
| Detail | What is established |
|---|---|
| Announcement date | December 2, 2024 |
| Financing | Series D; more than $693 million |
| Lead investors | Samsung Securities and AFW Partners |
| Valuation | $2 billion pre-money; approximately $2.7 billion post-money if the full announced amount is included |
| Bezos involvement | Bezos Expeditions participated |
Who Tenstorrent is
Tenstorrent is a Santa Clara-based semiconductor company associated with chip designer Jim Keller. It develops AI accelerators, processors, chiplet and interconnect technology, software tools and complete systems. That makes it broader than a company selling a single GPU product.
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- Dual-Brain Hybrid Power: Combines the Qualcomm Dragonwing QRB2210 MPU (Quad-core Arm Cortex-A53 @ 2.0 GHz CPU, Adreno GPU, AI acceleration) and the real-time, low-power STM32U585 MCU for advanced applications like object recognition, voice commands, and motion detection.
- AI & Linux Capabilities: Unlocks AI-powered vision and sound solutions; runs Linux Debian OS for coding in Python and supports the Arduino ecosystem with libraries and Sketches; quick start with Arduino App Lab.
- Advanced Features: Equipped with 4 GB LPDDR4 RAM, 32 GB eMMC built-in storage, ideal for single-board computer (SBC) mode, running multiple simultaneous high-level processes, more complex AI or ML models, extensive logs. Dual-band Wi-Fi 5 (2.4/5 GHz), Bluetooth 5.1, and high-speed headers for vision, audio, and display peripherals.
- Seamless Expansion & Connectivity: Features the classic UNO form factor for shields compatibility, an 8x13 LED matrix, and a Qwiic connector for easy expansion with Modulino nodes; power and connect via the USB-C connector.
- Intended Use & Development: The perfect platform for prototyping robotics or IoT projects, empowering innovators with a unified development experience to mix Arduino Sketches, Python scripts, and containerized AI models in a single interface.
Hardware and processor strategy
The company uses RISC-V technology in parts of its CPU and accelerator strategy and promotes chiplet-based designs. Its product portfolio therefore spans processor intellectual property and physical AI-computing systems, not just accelerator cards.
Software and developer tools
Tenstorrent is building an open-oriented software stack, including compiler and runtime layers, intended to give developers an alternative to closed accelerator ecosystems. “Open” does not mean automatic compatibility with every NVIDIA library or CUDA application; buyers still need to check model, operator, debugging and deployment support for their workloads.
Systems such as Galaxy
Tenstorrent’s Galaxy systems combine accelerators, memory, networking and system software for larger deployments. The company’s Galaxy page describes configurations scaling from four to 36 or more systems. These are company product specifications, not independent performance tests. Tenstorrent Galaxy
Why NVIDIA is the comparison
Tenstorrent is described as taking on NVIDIA because it is targeting the same broad AI-computing opportunity while emphasizing a different ecosystem strategy. NVIDIA’s strength is not only silicon. CUDA, optimized libraries, developer tools, cloud availability, system integration and a large installed base make its platform difficult to displace.
Tenstorrent’s proposed alternative combines RISC-V, more open software components and configurable systems. That may appeal to organizations seeking supply-chain flexibility, sovereignty, customization or less dependence on NVIDIA’s proprietary stack. Inference, specialized workloads and private AI infrastructure may offer more practical entry points than a claim to replace NVIDIA across all training workloads.
Rank #2
- Dual-Brain Hybrid Power: Combines the Qualcomm Dragonwing QRB2210 MPU (Quad-core Arm Cortex-A53 @ 2.0 GHz CPU, Adreno GPU, AI acceleration) and the real-time, low-power STM32U585 MCU for advanced applications like object recognition, voice commands, and motion detection.
- AI & Linux Capabilities: Unlocks AI-powered vision and sound solutions; runs Linux Debian OS for coding in Python and supports the Arduino ecosystem with libraries and Sketches; quick start with Arduino App Lab.
- Advanced Features: Equipped with 2 GB LPDDR4 RAM, 16 GB eMMC built-in storage, ideal to develop in PC-connected mode, running the OS, Python scripts, and basic network services (SSH) without a demanding GUI or heavy multitasking; great for lightweight AI and memory-optimized TinyML applications, needing local storage for basic OS and core libraries. Dual-band Wi-Fi 5 (2.4/5 GHz), Bluetooth 5.1, and high-speed headers for vision, audio, and display peripherals.
- Seamless Expansion & Connectivity: Features the classic UNO form factor for shields compatibility, an 8x13 LED matrix, and a Qwiic connector for easy expansion with Modulino nodes; power and connect via the USB-C connector.
- Intended Use & Development: The perfect platform for prototyping robotics or IoT projects, empowering innovators with a unified development experience to mix Arduino Sketches, Python scripts, and containerized AI models in a single interface.
The financing demonstrates investor confidence and strategic interest. It does not establish that Tenstorrent matches NVIDIA on performance, software maturity, manufacturing volume, customer base, revenue or support. A meaningful comparison requires the buyer’s own models, batch sizes, latency targets, utilization, memory requirements and total cost of ownership.
What Samsung’s role means
The lead investor named in the announcement was Samsung Securities, a Samsung financial-services entity. That is not the same as evidence that Samsung Electronics made a direct operating-company investment or has adopted Tenstorrent chips internally.
Samsung’s industrial connection also includes a separate foundry relationship. Tenstorrent announced that it selected Samsung Foundry to manufacture a next-generation AI chiplet in 2023. The foundry announcement concerns that chiplet; it should not be generalized to every Tenstorrent product.
Together, financing exposure and foundry cooperation could give Samsung-linked businesses a route into a growing AI-chip ecosystem. A successful Tenstorrent product could create future opportunities in manufacturing, packaging, supply and system partnerships. Nothing in the funding announcement shows that Samsung is abandoning NVIDIA.
What Bezos’s involvement means
The named investor was Bezos Expeditions, Jeff Bezos’s investment organization. The announcement does not establish that Bezos personally wrote a separate direct check, runs Tenstorrent, advises its engineering team or that Amazon has an operating partnership with the company. The supported conclusion is narrower: Bezos Expeditions participated in the financing.
Rank #3
- Single core ARM Cortex-A7 32-bit core, integrated with NEON and FPU
- Built in Micro's self-developed 4th generation NPU, with high computational accuracy and support for mixed quantization of int4, int8, and int16. Among them, int8 has a computing power of 0.5 TOPS and int4 has a computing power of up to 1.0 TOPS
- Built in self-developed 3rd generation ISP3.2, supports 4 million pixels, and supports various image enhancement and correction algorithms such as HDR, WDR, and multi-level denoisin
- It has powerful encoding performance, supports intelligent encoding, adapts to save bit rates according to the scene, and saves more than 50% of the bit rate compared to conventional CBR mode, making the captured images high-definition, smaller in size, and doubling the storage space
- The design with built-in RISC-V MCU supports low-power fast startup, 250ms fast capture, and simultaneous loading of AI model library, enabling facial recognition to be completed within 1 second
What Tenstorrent said the money would fund
According to the announcement, proceeds were intended to support:
- Expansion of the engineering team.
- Supply-chain investment.
- Construction of AI training servers used to demonstrate Tenstorrent technology.
- Global development and design expansion.
These were planned uses of proceeds, not proof that every project had already been completed.
What happened after the 2024 round
Tenstorrent’s newsroom lists substantial subsequent activity. The company announced Blackhole developer products on April 3, 2025, and said Wormhole instances became available through Koyeb in February 2025. It later announced a compact AI accelerator in January 2026, sovereign-AI infrastructure partnerships, Galaxy Blackhole performance and deployment updates, the TT-Ascalon S processor and expansion across Japan on June 30, 2026, and a runtime-observability partnership on July 30, 2026. Tenstorrent’s newsroom archive
Those are company announcements. Performance, customer, deployment and partnership statements should be read as Tenstorrent’s claims unless an independent customer disclosure or test confirms them. Tenstorrent’s own scale-performance material is useful for understanding its positioning, but it is not a substitute for independently reproduced benchmarks. Company performance announcement
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What a serious buyer should verify
An enterprise considering Tenstorrent should evaluate the complete platform rather than the accelerator name alone:
Rank #4
- 【POWERFUL ESP32‑S3 CONTROLLER】Built‑in Xtensa 32‑bit LX7 dual‑core processor, 512KB SRAM, 8MB PSRAM, 16MB Flash for stable AI voice computing and multitask processing.
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- 【STABLE WIRELESS & CLEAR AUDIO】Integrated 2.4GHz Wi‑Fi + Bluetooth 5 (LE); dedicated audio decoding module for natural, responsive voice interaction.
- 【USER‑FRIENDLY VISUAL & PLUG‑AND‑PLAY】2” TFT‑SPI color screen shows real‑time chat; modular design, no extra wiring, ready to use after setup.
- 【FULL LEARNING SUPPORT】45 programmable GPIOs, rich interfaces, online web tutorials, free technical support for beginners & developers.
- Which models and operators run natively, and what code changes are required to port CUDA workloads?
- Is the target use case training, inference, video generation or another specialized workload?
- What latency, throughput, utilization, memory capacity and bandwidth result under the buyer’s actual batch sizes?
- What networking fabric, cooling, power delivery and systems software are required at cluster scale?
- Who provides installation, technical support, replacement hardware and long-term software maintenance?
- Are benchmarks independently reproduced, and are the compared systems configured fairly?
- What are the delivery timeline, geographic availability and any export-control constraints?
Public pricing for Galaxy, Blackhole developer hardware and current cloud access was not established in the available company material. Buyers should obtain current quotations and service terms directly rather than assume a standard retail price.
The investment’s significance—and its limits
The round gives Tenstorrent capital to expand engineering, supply and demonstration infrastructure while adding strategically relevant investors. It also links the company to Samsung’s financial and foundry ecosystem and to Bezos Expeditions.
It does not prove production volume, recurring revenue, market share, customer concentration, cost superiority or software parity with CUDA. Those commercial metrics remain undisclosed or independently unverified in the available material. The defensible interpretation is that Tenstorrent is seeking a larger share of AI infrastructure as an alternative platform—not that the financing has already created an NVIDIA replacement.
Bottom line
“Samsung joins Jeff Bezos to put $700 million in an AI chipmaker” compresses a more precise story: Samsung Securities and AFW Partners led a Series D of more than $693 million, Bezos Expeditions participated, and Tenstorrent is pursuing AI accelerators, RISC-V technology, open-oriented software and scalable systems. The deal materially strengthens Tenstorrent’s ability to compete for selected AI workloads, but funding alone does not demonstrate that it can match NVIDIA’s ecosystem or market position.
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