Robot model
Zhikai-100
7nm GPGPU chip for AI inference, design completed May 2022.
- Manufacturer
- Iluvatar CoreX
- Form factor
- other
- Maturity
- production
- Lifecycle
- active
The verified answer
As of Aug 2026, DEPLOY verifies Zhikai-100, a other by Iluvatar CoreX (production). 1 source back the record.
Overview
7nm GPGPU chip for AI inference, design completed May 2022. Companion to the TianGai-100 training chip, targeting inference workloads in cloud and data center environments.
Verified vs. claimed
- Maturity stage
- production(Full-scale production deployment with repeat customers.)
- Sources on file
- View all sources →
Data & sources
Web sources
1
1 source backing this record.View all →
Pricing
No verified price is on record for Zhikai-100. Physical-AI systems are often sold through enterprise contracts or operated as a service rather than at a public list price.
Recent activity
Every change to this record is dated, sourced, and independently verified where marked.
- Record createdAug 25, 2026
Added to the verified registry
Safety record
No incidents on record for Zhikai-100.
Only active incidents are counted. Retracted incidents are excluded from this summary but remain reachable at their canonical URLs.
Sources (1)
- Iluvatar CoreX · https://en.wikipedia.org/wiki/Iluvatar_CoreX
Common questions
What is Zhikai-100?
How much does Zhikai-100 cost?
Is Zhikai-100 actually deployed in the real world?
Who makes Zhikai-100?
Can you buy Zhikai-100?
What are alternatives to Zhikai-100?
How does Zhikai-100 compare to 10Beauty Manicure System?
What is Zhikai-100's maturity stage?
Where is Zhikai-100 deployed?
Is Zhikai-100 safe?
Methodology: Unreviewed · 1 source (no primary) · last reviewed 2026-08-25
Verification posture
Unreviewed
Low confidence
Review state
Stable
Last reviewed 2026-08-25
Maturity + lifecycle
Maturity stage: production
Lifecycle: active
Architectural position
Cohort: other
Sources by quality tier
- 1
- knowledge-base
- Knowledge base
The framework is documented at /methodology. Corrections at /corrections. Reviewer: DEPLOY editorial team.
Methodology surface for Zhikai-100.Machine-readable surfaces
- Markdown mirror: /models/zhikai-100.md
- JSON-LD: embedded in this page’s head
- REST API: /v1/models/874aab92-705a-4dcb-bbd8-72267ed58268
- Revision history: /models/zhikai-100/history
- Data documentation: /data
- Query this programmatically: Deploy MCP