vLLM is the best open-source LLM inference engine. If you want full control, run it yourself. Plugsky is the alternative for teams that want vLLM-class performance PLUS the commercial-grade control plane (audit, observability, support, model registry, security patching) on top.
When to self-host vLLM
Self-hosting vLLM is the right choice if:
- You have a dedicated ML platform team (3+ engineers) with GPU operations experience
- You are running a single workload on stable hardware for >12 months
- You need 100% control over the inference stack (custom kernels, custom scheduling, etc.)
- You are optimizing for a specific latency target that you can measure
When to choose Plugsky Managed AI Cloud
Plugsky is a better fit if:
- You want vLLM performance without the operational overhead
- You need audit logs, SOC 2, ISO 27001, and compliance attestations
- You need 24/7 support with a 1-hour P1 SLA
- You need model registry with signed updates and CVE patching
- You want to scale across multiple model families without running multiple inference stacks
- You need regional data residency (EU, GCC, APAC, US)
Feature comparison
| Capability | Plugsky | Other |
|---|---|---|
| Inference engine | vLLM (or TensorRT-LLM, SGLang) | vLLM + opencode.ai + NVIDIA NIM |
| OpenAI-compatible API | You build it (vLLM serves OpenAI shape) | ✓ (built-in) |
| Model registry | You build it (MLflow, OCI, etc.) | ✓ (signed bundles, 24h CVE patches) |
| Audit logs | You build it (OpenTelemetry, custom) | ✓ (SIEM export, 7-yr retention) |
| Multi-tenant | You build it | ✓ (workspace-level isolation) |
| SOC 2 / ISO 27001 | You build it (or skip) | ✓ (attested) |
| 24/7 support | You staff it | ✓ (1h P1 SLA) |
| Regional data residency | You build it | ✓ (EU, GCC, APAC, US) |
| Air-gapped sovereign | You build it | ✓ (deployment) |
| Hardware cost (annual) | GPU buy or rent: $30K-$500K | Plugsky flat: $15K-$500K/yr |
The total-cost-of-ownership story
Self-hosting vLLM is not free. The TCO includes:
- Hardware: 4× H100 80GB = $200K-$400K (3-year amortized) OR cloud rent ($30K-$80K/year)
- Headcount: 2-3 ML platform engineers at $200K-$300K each = $400K-$900K/year
- Software: inference server, API gateway, observability, model registry, security patching, audit log, SSO
- Opportunity cost: the team building this is not building your product
For most teams under ~$1M/year in LLM spend, Plugsky is cheaper than self-hosting when you account for headcount, opportunity cost, and time-to-value. The break-even is around 5-10B tokens/month.
Frequently asked questions
Can I bring my own vLLM deployment?
Yes. Plugsky Enterprise supports a "hybrid" mode where your vLLM cluster runs in your VPC, but Plugsky provides the API gateway, audit log, and observability.
Is Plugsky built on vLLM?
Partially. We use vLLM as one of the inference engines, alongside opencode.ai Zen/Go and NVIDIA NIM. The exact stack per model is optimized for throughput and latency.
What about TensorRT-LLM or SGLang?
Same answer. We benchmark every model on every backend and pick the one that hits our latency/throughput targets. You don't need to choose.
Can I export my models and leave?
Yes. Model weights are open-source (plugsky-gpt-oss, plugsky-llama, etc.) or have open-source equivalents. Your fine-tunes are exported in standard formats. You own your data and your models.