Inference-first TPU pods
- Version
- 7th-generation (Ironwood)
- Cost
- from $5.4/unit
- Model
- Gemini
d-Matrix · #13 most active of 18 in Chips & Compute
Digital in-memory compute for inference efficiency.
Current version
Corsair
Entry cost
System sales
Changes / 30d
0
The short answers
Source: d-Matrix (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.
Inference-first TPU pods
Cerebras
Wafer-scale inference and training
Tenstorrent
Open RISC-V AI hardware
Cloud-native training silicon
NVIDIA
GB200/B200 rack-scale AI systems
High-memory GPU alternative
Products in other segments that name one of d-Matrix Corsair'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/d-matrix
Tomorrow. (2026). d-Matrix Corsair — version, pricing and model stack [Data set entry]. AlienSquad. Retrieved 2026-11-08, from https://tomorrow.aliensquad.ai/tools/d-matrix
@misc{tomorrow-tools-d-matrix,
author = {{Tomorrow}},
title = {d-Matrix Corsair — version, pricing and model stack},
year = {2026},
publisher = {AlienSquad},
howpublished = {\url{https://tomorrow.aliensquad.ai/tools/d-matrix}},
note = {Accessed: 2026-11-08}
}