Model-serving infrastructure
vLLM can serve compatible language models for self-hosted coding-agent workloads, but serving is only one layer. Teams must also manage model suitability, context, tool execution, concurrency, repository permissions, evidence and review. Nexus can treat a vLLM-backed model route as a worker beneath the same governance layer.
A model endpoint supplies inference. An engineering worker additionally needs prompts, tools, workspace isolation, timeouts and a contract for returning code and evidence.
The control plane must decide which work the worker owns and whether its result is current.
Batching improves throughput but can increase latency. Long contexts compete for memory, and aggressive concurrency can produce queues that obscure delivery time.
Benchmark with representative repository tasks and include review quality, not only tokens per second.
Nexus can route appropriate tasks to approved self-hosted model infrastructure while storing authority outside the model server.
vLLM availability does not remove exact-SHA review, fencing or human release controls; it changes an execution route.
Nexus launch access
Register your interest now and we will let you know when the autonomous AI software engineering control plane is ready.
