# TuringData Launches ContextCube at Tech Week Singapore 2026, Bringing Shared KV Cache to GPU Inference Clusters

- Link: https://www.thailand-business-news.com/pr-news/turingdata-launches-contextcube-at-tech-week-singapore-2026-bringing-shared-kv-cache-to-gpu-inference-clusters
- Published: 2026-09-29T09:00:00+07:00
- Author: PR Newswire

SINGAPORE, Sept. 29, 2026 /PRNewswire/ — TuringData today launched ContextCube, 
a purpose-built KV cache appliance that gives AI inference clusters a shared, persistent
pool of context.

Unveiled at Tech Week Singapore 2026, ContextCube enables participating inference
nodes to retrieve matching cached KV over RDMA instead of repeatedly computing or
storing the same context. This reduces time to first token, frees GPU cycles for
token generation and supports greater throughput and concurrency.

As prompts grow longer and requests move between servers, valuable KV cache is often
evicted or becomes inaccessible because it is held locally. ContextCube addresses
this challenge by making previously computed context reusable across the cluster.

Designed on the NVIDIA CMX inference-storage reference architecture, ContextCube
adds a shared Layer 3.5 alongside GPU HBM, DRAM and local NVMe storage. Active computation
remains on GPUs while reusable context is retained in a large, cluster-wide cache.

[⌊TuringData launched ContextCube, a KV cache appliance that gives AI inference 
clusters a shared, persistent pool of context, at Tech Week Singapore 2026. (Photo:
TuringData)⌉⌊TuringData launched ContextCube, a KV cache appliance that gives AI
inference clusters a shared, persistent pool of context, at Tech Week Singapore 
2026. (Photo: TuringData)⌉[
TuringData launched ContextCube, a KV cache appliance
that gives AI inference clusters a shared, persistent pool of context, at Tech Week
Singapore 2026. (Photo: TuringData)

Key capabilities include:

 ◦ Hundreds of terabytes of shared KV cache, with retention ranging from hours to
   weeks depending on configuration, workload and cache policy
 ◦ 120 GB/s KV bandwidth per appliance*
 ◦ DPU-based data movement using four NVIDIA BlueField-3 DPUs
 ◦ 26 U.2 NVMe drives and two 200 Gb/s ports per DPU
 ◦ Compatibility with inference engines including vLLM and SGLang, and KV cache 
   software including TuringData Cache Fabric, LMCache and Mooncake
 ◦ Starting deployments from one appliance

ContextCube is designed for context-intensive workloads, including AI agents, coding
assistants, multi-turn conversations, long-document processing, retrieval-augmented
generation and large-scale "token factories."

"As context windows grow and AI agents move into production, the same context is
being computed again and again on every server," said Jenvik Li, Founder and CEO
of TuringData. "ContextCube gives the whole cluster one place to keep that work,
so GPUs can spend their time generating new tokens instead of rebuilding old ones."

ContextCube is available to order now. Visit [www.turingdata.io/contact-us](http://www.turingdata.io/contact-us).

**About TuringData**

Headquartered in Singapore, TuringData builds the data layer for AI infrastructure,
helping enterprises and AI cloud providers improve GPU utilisation and token economics
across training and inference. Learn more at [www.turingdata.io](http://www.turingdata.io/).

_*Actual performance depends on configuration and workload. NVIDIA and BlueField
are trademarks and/or registered trademarks of NVIDIA Corporation in the United 
States and other countries._

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