Reserved Deployments provide dedicated GPU clusters tailored to your specific infrastructure needs — guaranteed capacity, consistent performance, and no resource contention. Navigate to Deploy → Reserved to submit a request.Documentation Index
Fetch the complete documentation index at: https://docs.tensormesh.ai/llms.txt
Use this file to discover all available pages before exploring further.
When To Use Reserved
High-Volume Production
Workloads that require consistent throughput at a scale where serverless costs exceed a flat cluster rate.
Latency SLAs
Applications with strict latency requirements that need dedicated, non-shared GPU resources.
Enterprise Compliance
Deployments that require data isolation, custom networking, or specific compliance guarantees.
Tailored Pricing
A flat cluster rate replaces variable per-token billing — easier to budget at scale and priced to your specific workload and capacity requirements.
Requesting a Cluster
Submit a request through the form at Deploy → Reserved. Provide your cluster specifications: GPU Selection — Choose between high-compute GPU optionsCluster Size — Define the total number of GPUs required for your workload
Timeline — Specify your deployment window
Use Case — Describe the intended workload