Specifications
Model
Blackhole p100a
Vendor
Tenstorrent
Architecture
Tensix (RISC-V)
Tensix Cores
120
Big RISC-V Cores
16 per Blackhole processor
Memory
28 GB GDDR6
TDP
Up to 300 W
Form Factor
PCIe card, active cooling, desktop workstation
Host Interface
PCIe Gen5 x16
Process Node
TSMC 6 nm (Blackhole processor)
Memory Type
GDDR6 (up to 32 GB per chip on p150-class boards)
Software Stack
TT-Metalium / TT-NN - fully open source
Developer Access
Full access to the metal through the open-source stack
Scalability
Blackhole PCIe boards link together to pool memory and scale performance
Scale-Out Interconnect
QSFP-DD 800G passive ports on the p150a variant
Line Positioning
Entry price point of the Blackhole PCIe family
Availability
Ships in 2 weeks; transit 2-5 weeks
Overview
The Tenstorrent Blackhole p100a is the entry point of the Blackhole PCIe card line, priced below the p150a and p150b. It uses the same Blackhole Tensix processor - 120 Tensix cores plus 16 big RISC-V management cores - with 28 GB of GDDR6 and a thermal design power of up to 300 W in an actively cooled form factor aimed at desktop workstations.
What distinguishes the Blackhole family is the software position: Tenstorrent ships the complete TT-Metalium and TT-NN stack as open source, so developers get full access to the hardware rather than a closed runtime. Blackhole PCIe boards are designed to be linked together to pool memory and improve performance, and the p150a variant adds four passive QSFP-DD 800G ports for direct card-to-card scaling.
Key Benefits
Open, not locked in. TT-Metalium and TT-NN are fully open source with access to the metal - an alternative to closed accelerator runtimes. Low entry cost. The p100a is the most affordable route into the Blackhole PCIe family. Scale-out by design. Blackhole cards link together to pool memory and scale workload performance. RISC-V foundation. Tensix cores with 16 big RISC-V management cores per processor.
Applications
Deskside LLM and model development, RISC-V and open-source AI research, academic and lab AI workstations, inference and training experimentation, and scale-out Blackhole clusters.
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