Guaranteed performance,
on the models you choose
Single-tenant AI inference hardware, reserved exclusively for you in Infercom's EU data centers and fully operated by us. No other tenants competing for throughput, a predictable monthly cost, and your own mix of models - including ones beyond the public catalog.
Same platform, more control
The same sovereign platform - reserved for you alone
Dedicated Capacity runs the same OpenAI-compatible API, same EU sovereignty, and same full-precision inference as our shared Inference API - but on single-tenant hardware nobody else touches. You get guaranteed, contention-free throughput for a predictable monthly cost, and you can run your own selection of models, including ones beyond the public catalog.
The Fit
When to choose Dedicated Capacity
It pays off once your workload is high, steady, and production-critical. Below that, the shared API is usually the better deal - and we'll say so.
High, steady volume
Sustained production traffic that consistently pushes past what the shared tiers economically cover.
Guaranteed SLAs
Contractual uptime and response-time commitments, with no contention from other tenants.
Custom models
Run fine-tuned checkpoints (BYOC) or multiple models on one rack, switched in milliseconds.
Isolation
Single-tenant hardware for compliance, predictable performance, or peace of mind.
What You Get
A production inference engine, run for you
Your own high-throughput AI inference plant - serving models at production scale, with sovereign, single-tenant infrastructure that Infercom deploys, operates, and keeps running so your team can focus on building, not ops.
Infrastructure
- Single-tenant hardware reserved for you - one rack or many
- Fully operated and maintained by Infercom
- Guaranteed throughput - no noisy neighbours
- Custom rate limits, or none at all
- Full precision, no quantization
- In Infercom's EU data centers, with zero data retention
Support & SLAs
- Dedicated account team
- Priority support with direct escalation
- Custom SLAs (uptime, response time)
- Right-sizing from your real workload
- ISO 27001 certified operations
- Deployment typically within ~2 weeks
Models
Run the models you need
A dedicated rack can run models beyond the public API catalog - including ones we bring up specifically for you - plus your own fine-tuned checkpoints via Bring Your Own Checkpoint.
- The full public catalog, at full precision
- Models beyond the public catalog, brought up on request
- BYOC - fine-tunes of supported architectures load immediately
- Up to ~700B parameters on a single rack
Fine-tunes of supported architectures load immediately; genuinely new architectures are a commercial conversation. We won't promise a specific custom model without checking it can run.
Available on your rack
Fine-tuning itself runs on GPUs - you train, then hand us the weights to serve at full speed.
View full model catalogOne rack, many models
Switch checkpoints in milliseconds
Because memory sits directly on the chip, a dedicated rack can hold several models and fine-tuned checkpoints at once - and switch between them in under 600 milliseconds, versus the seconds-to-minutes a GPU cluster needs.
That means one rack can serve a whole agentic pipeline - a planner model, an executor, and a specialised fine-tune - switching per step without standing up separate infrastructure for each.
How many models fit on a rack at once depends on their size - we'll size it to your mix.
Comparison
Dedicated Capacity vs Inference API
| Inference API | Dedicated Capacity | |
|---|---|---|
| Infrastructure | Shared (multi-tenant) | Reserved (single-tenant) |
| Billing | Pay-per-token | Flat monthly |
| Rate limits | Tier-based | Custom or none |
| Contention | Shared queue under load | None - it's all yours |
| Custom models (BYOC) | Catalog only | Catalog + your checkpoints |
| Support | Tier-based | Dedicated team |
| SLAs | Best-effort | Custom, guaranteed |
FAQ