AI Inference Workstations

Junhangclaw series · 50 TOPS to 2070 TFLOPS · personal to enterprise

The Junhangclaw personal super-workstation series spans four tiers, from a 50 TOPS domestic-silicon entry model to the flagship JH-W2000 with an NVIDIA Blackwell GPU delivering 2070 TFLOPS (FP4 sparse) — built for local AI inference where private data never leaves the premises.

Product Models

Specification Comparison

JH-W50
Type: 50 TOPS
Interface: Entry
Config: 50 TOPS
Domestic silicon · 50 TOPS · personal users
JH-W120
Type: 120 TOPS
Interface: Enhanced
Config: 120 TOPS
120 TOPS · small teams
JH-W280
Type: 280 TOPS
Interface: Professional
Config: 280 TOPS INT8
MetaX domestic silicon · 280 TOPS INT8 · localization-ready
JH-W2000
Type: 2070 TFLOPS
Interface: Flagship compact
Config: 128GB · 1TB
Blackwell GPU · 2070 TFLOPS FP4 sparse · 128GB unified memory
JH-W2000N
Type: 2070 TFLOPS
Interface: Flagship expanded
Config: 128GB · 1TB+4bay
Blackwell GPU · 2070 TFLOPS · 4× 2.5-inch bay expansion
Four compute tiers from 50 TOPS to 2070 TFLOPS (FP4 sparse)
Domestic silicon and NVIDIA Blackwell tracks
Local AI inference — private data stays on-premises
Flagship 128GB LPDDR5x unified memory and 25GbE networking
Desktop liquid cooling (140mm radiator on the flagship)

Specifications as of ; see each model page and the official product guide for details.

Frequently Asked Questions

Which models and compute tiers are available?

Five models: JH-W50 entry at 50 TOPS, JH-W120 enhanced at 120 TOPS, JH-W280 professional at 280 TOPS (INT8), and the flagship JH-W2000 and JH-W2000N at 2070 TFLOPS (FP4 sparse).

What is in the flagship JH-W2000?

NVIDIA Blackwell GPU, 14-core Arm Neoverse, up to 128GB LPDDR5x unified memory, 1TB NVMe, 140mm radiator liquid cooling, up to 4× 25GbE and a 300W external adapter; the JH-W2000N adds a four-bay 2.5-inch storage module.

Who are these workstations for?

JH-W50 for personal users, JH-W120 for small teams, JH-W280 (MetaX domestic silicon) for government and enterprise localization, and JH-W2000/W2000N for LLM inference, enterprise agents and knowledge bases, all for local inference where private data stays on-premises.

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