Hub 02 · Self-hosted GPU economics

Self-hosted GPU economics for AI coding agents.

Nexus separates the software delivery contract from the model provider. That lets teams route sustained coding workloads to local GPUs, retain API elasticity where it adds value and compare both using verified delivery economics.

Can autonomous coding models run on private infrastructure?

Yes. Sustained or sensitive coding workloads can run on self-hosted GPU capacity while approved external APIs remain available for selected roles or demand peaks. Nexus keeps the engineering evidence and governance contract consistent across both.

Technical article

Local GPU Cluster vs. Cloud LLM APIs for Parallel Coding Agents

Cloud APIs buy elastic capacity and rapid model access; local GPUs buy predictable marginal cost, data locality and scheduling control. Nexus treats models as replaceable workers behind a stable delivery contract, so sensitive or high-volume coding lanes can use local inference while selected reasoning gates can still use approved APIs. The decision is made per role and workload, not as an all-or-nothing platform bet.

Model route per specialist role
Fixed local capacity for sustained workloads
Elastic API capacity for peaks or specialist review
One evidence and governance contract across both

Technical article

Optimizing vLLM Continuous Batching for Concurrent Coder Streams

Continuous batching improves GPU utilisation by admitting new requests as existing sequences finish. Coding workloads need explicit concurrency, context-length and token-budget limits so one large repository task cannot starve every other lane. Nexus schedules bounded tranches, records queue time and separates generation throughput from verified delivery throughput.

Bound context and output budgets
Group compatible model workloads
Measure queue delay and tokens per second
Protect reviewer capacity from builder saturation

Technical article

Calculating Fixed GPU Overhead vs. Variable Token Spend

Compare infrastructure on useful reviewed output, not raw token price. A local server has a fixed monthly cost and a capacity ceiling; APIs have variable usage cost and near-elastic burst capacity. Nexus exposes the work, review and integration states needed to calculate cost per clean integrated tranche.

Local unit cost = monthly GPU overhead ÷ clean integrated tranches
API unit cost = model spend ÷ clean integrated tranches
Include reviewer and remediation consumption
Track idle capacity and peak spillover separately

Decision metric

Cost per verified delivery

Unit delivery costModel + infrastructure spend÷clean integrated tranches

Explore self-hosted Nexus infrastructure ↗AI agent governance All technical resources

Nexus launch access

Be first to know when Nexus launches.

Express Interest ↗