DEDICATED GPU CAPACITY
202 Compute owns, hosts, and operates GPU systems for qualified commercial workloads. We work directly with customers on capacity, environment, term, access, and support requirements.
01 / Available compute
Our custom dual-GPU pod packages two NVIDIA RTX 5090 accelerators with the host CPU, system memory, NVMe storage, cooling, power delivery, remote access, and monitoring needed for sustained workloads.
202 / DUAL BLACKWELL POD
WHAT ONE POD CAN SUPPORT
Actual fit depends on model architecture, precision, context length, batching, framework overhead, and whether the workload supports multiple GPUs.
Up to approximately 70B-class quantized models when the runtime supports tensor parallelism across both GPUs.
Run separate services on each 32 GB GPU—for example, multiple smaller language, vision, embedding, or reranking models.
LoRA and QLoRA adaptation, evaluation suites, and experimentation for appropriately sized models and datasets.
High-throughput image, video, 3D, simulation, and CUDA-enabled production pipelines.
Commercial terms define the environment, usage window, access model, support scope, and expected utilization.
Host CPU, system memory, and storage are documented in the capacity proposal for each deployment.
202 Compute houses the pod, observes component health, and coordinates infrastructure maintenance.
Add capacity through additional pods or transition into a larger professional GPU configuration.
02 / Workload fit
We evaluate each engagement for technical fit before reserving hardware.
Dedicated accelerators for APIs, agents, vision, language, and other production inference workloads.
Isolated compute for model adaptation, evaluation, and iterative development.
GPU capacity for qualified 3D, video, visualization, and generative-media workloads.
Longer-term infrastructure arrangements for companies that need predictable access.
03 / Capacity roadmap
New configurations are planned around customer demand. Future systems are not represented as currently available; companies can discuss requirements and potential reservations now.
Compact dedicated capacity for inference, adaptation, rendering, and parallel GPU services.
Professional Blackwell capacity for larger models, higher concurrency, scientific computing, simulation, and enterprise workloads.
Higher GPU counts, networking, storage, and deployment design developed against a qualified contract requirement.
04 / Engagement models
PROJECT
Capacity reserved for a specific project, run, or delivery window.
RESERVED
Predictable dedicated access for ongoing workloads and development teams.
CUSTOM
A tailored deployment covering hardware, environment, utilization, support, and term.
CAPACITY REQUEST
Include your preferred GPU count, software stack, utilization pattern, storage needs, start date, and contract term.