Tenstorrent
Open RISC-V AI hardware
- Version
- Blackhole
- Cost
- from $999/unit
- Model
- Tensix cores
FuriosaAI · #15 most active of 18 in Chips & Compute
Korean inference silicon with strong perf-per-watt.
Current version
RNGD
Entry cost
System sales
Changes / 30d
0
The short answers
Source: FuriosaAI (no public source page recorded) · Reusable under CC BY 4.0 — cite Tomorrow
System sales
Entry price over time
Not enough pricing history yet — we start charting from the second observation.
n/a
Provider undisclosed
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.
Tenstorrent
Open RISC-V AI hardware
Inference-first TPU pods
Cerebras
Wafer-scale inference and training
NVIDIA
GB200/B200 rack-scale AI systems
Cloud-native training silicon
Intel
Cost-focused training and inference accelerator.
Products in other segments that name one of FuriosaAI RNGD's models in their stack.
Fivetran
Managed pipelines feeding the AI data layer.
Vertical AerospaceEU
UK eVTOL programme in piloted flight testing.
No changes recorded yet.
Straight 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/furiosa
Tomorrow. (2026). FuriosaAI RNGD — version, pricing and model stack [Data set entry]. AlienSquad. Retrieved 2026-09-17, from https://tomorrow.aliensquad.ai/tools/furiosa
@misc{tomorrow-tools-furiosa,
author = {{Tomorrow}},
title = {FuriosaAI RNGD — version, pricing and model stack},
year = {2026},
publisher = {AlienSquad},
howpublished = {\url{https://tomorrow.aliensquad.ai/tools/furiosa}},
note = {Accessed: 2026-09-17}
}