engineering · 1 min read
Open-Source Models Through the Gateway: vLLM, Ollama and TGI
Open-source models on your own GPUs are 5-20× cheaper for the right workloads. Here is how Bhogar AI lets you mix them with hosted providers.
BABhogar AI TeamProduct & Engineering
Open-source models on your own GPUs are dramatically cheaper for the right workloads. Mixing them with hosted providers gives you the best of both - and the gateway is what makes it operational.
Why it matters
Self-hosted endpoints have different scaling characteristics, different reliability profiles and different feature sets. Treating them as just another route in the gateway absorbs that complexity.
How Bhogar AI approaches it
Bhogar AI gateway supports vLLM, Ollama, TGI and any OpenAI-compatible endpoint as first-class providers, with the same routing, fallback, observability and quotas as hosted ones.
- First-class support for vLLM, Ollama, TGI and OpenAI-compatible endpoints
- Routing on cost, latency and capability
- Auto-fallback to hosted on local saturation
- Same observability across hosted and self-hosted
- Compatible with KEDA-driven GPU autoscaling
What you get
Customers running hybrid hosted + self-hosted setups behind the gateway commonly cut LLM spend 40-70% on classifier-style workloads.