Inference-first TPU pods
- Version
- 7th-generation (Ironwood)
- Cost
- from $5.4/unit
- Model
- Gemini
Tenstorrent · #3 most active of 18 in Chips & Compute
Open-source software stack and RISC-V based accelerators sold as cards and IP.
Trust score · Mostly verified
3 data points checked · 2026-11-03
Current version
Blackhole
Entry cost
from $999/unit
Changes / 30d
8
The short answers · verified November 6, 2026
Source: Tenstorrent — github.com · Reusable under CC BY 4.0 — cite Tomorrow
Cards
Passive, active and liquid cooling options
$999
Workstations
Whisper-quiet, liquid cooled - run models up to 120b parameters from your desk
$9999
Servers (Tenstorrent Galaxy)
Sovereign, scale-out servers for production AI
$70000
Entry price over time
Blackhole Tensix
Tenstorrent
Gemma-2
Gemma4
GLM-5.2
Zhipu AI
Kimi-K3
Moonshot AI
Llama-3.3-70B
Meta
Qwen3-32B
Alibaba
Tensix cores
Tenstorrent
tt-metal / tt-nn
Tenstorrent
Context window
—
Public API
no
Multi-model routing
no
Other tracked products running on the same foundation models — a quick read on how much of the catalog moves when one of these models changes.
green disclosed · amber inferred · grey unattributed. Aliases are folded into one model; provider concentration counts only models with an established vendor.
Reference data. Each figure is whatever the source actually said — weekly users, downloads, revenue run-rate — with its own definition and date. These are not comparable between tools and are never used to rank anything.
No public usage figure on record for this product.
Inference-first TPU pods
Cerebras
Wafer-scale inference and training
Cloud-native training silicon
NVIDIA
GB200/B200 rack-scale AI systems
High-memory GPU alternative
Groq
Deterministic low-latency inference
Tenstorrent Blackhole added Blackhole Tensix to its model stack
GLM-5.2, Gemma-2, Gemma4, Kimi-K3, Llama-3.3-70B, Qwen3-32B, Tensix cores, tt-metal / tt-nnBlackhole Tensix, GLM-5.2, Gemma-2, Gemma4, Kimi-K3, Llama-3.3-70B, Qwen3-32B, Tensix cores, tt-metal / tt-nn
sourceNew capabilities: Liquid Cooling Options, PCIe Card Support, Scale-out Servers
144 tracked147 tracked · +Liquid Cooling Options, PCIe Card Support, Scale-out Servers
sourceNew capabilities: open-source software stack
143 tracked144 tracked · +open-source software stack
sourceNew capabilities: Liquid-cooled Workstation, Enterprise-class AI Server
141 tracked143 tracked · +Liquid-cooled Workstation, Enterprise-class AI Server
sourceNew capabilities: Enterprise Servers (Galaxy), MLIR-based Software Stack
139 tracked141 tracked · +Enterprise Servers (Galaxy), MLIR-based Software Stack
sourceNew capabilities: AI processor, Liquid-cooled Workstation format, Server format
135 tracked138 tracked · +AI processor, Liquid-cooled Workstation format, Server format
sourceNew capabilities: MLIR compiler, PCIe Card format, QuietBox workstation compatible
131 tracked135 tracked · +MLIR compiler, PCIe Card format, QuietBox workstation compatible, Galaxy server compatible
sourceNew capabilities: Liquid cooled workstation options
130 tracked131 tracked · +Liquid cooled workstation options
sourceNew capabilities: Scalable AI server option
129 tracked130 tracked · +Scalable AI server option
sourceNew capabilities: Liquid Coled Workstation, Ethernet routing
125 tracked127 tracked · +Liquid Coled Workstation, Ethernet routing
sourceNew capabilities: Metalium C++ SDK, TT-NN API
123 tracked125 tracked · +Metalium C++ SDK, TT-NN API
sourceNew capabilities: Deep Learning, LLM Serving, Low-Level Kernel Support
120 tracked123 tracked · +Deep Learning, LLM Serving, Low-Level Kernel Support
sourceNew capabilities: Metalium SDK support, TT-NN API support, Liquid cooling option
117 tracked120 tracked · +Metalium SDK support, TT-NN API support, Liquid cooling option
sourceNew capabilities: Workstation system support
115 tracked116 tracked · +Workstation system support
sourceStraight head-to-head pages against the busiest products in Chips & Compute.
Free to cite and reuse under CC BY 4.0. Permalink: https://tomorrow.aliensquad.ai/tools/tenstorrent
Tomorrow. (2026). Tenstorrent Blackhole — version, pricing and model stack [Data set entry]. AlienSquad. Retrieved 2026-11-08, from https://tomorrow.aliensquad.ai/tools/tenstorrent
@misc{tomorrow-tools-tenstorrent,
author = {{Tomorrow}},
title = {Tenstorrent Blackhole — version, pricing and model stack},
year = {2026},
publisher = {AlienSquad},
howpublished = {\url{https://tomorrow.aliensquad.ai/tools/tenstorrent}},
note = {Accessed: 2026-11-08}
}