The
platform.
GPU capacity. Model inference.
Dedicated infrastructure.
01 / GPU CLOUD
For the
whole model.
AMD Instinct capacity for training, fine-tuning and inference. Define the model, memory requirements and software stack before choosing the configuration.
- Dedicated GPU capacity planning
- ROCm compatibility assessment
- Application-level evaluation
02 / TOKEN FACTORY
From model
to endpoint.
API-based serving for open-weight models. Start with the model you need, the traffic you expect and the response time your application requires.
- Model and API requirements
- Latency and throughput targets
- Usage and commercial scoping
INFERENCE PLANNING
ModelOpen-weight LLM
InputYour application workload
TargetLatency · throughput · cost
03 / PRIVATE & ENTERPRISE
A deployment.
On your terms.
Dedicated infrastructure scoped around data location, security review and procurement requirements. Evaluate the design before agreeing the rollout.
- Dedicated cluster design
- Data location requirements
- Engineering-led scoping
Configuration, availability and commercial terms are confirmed through your proposal. Data centre photography is illustrative.
CONTACT