Nebius and NVIDIA tool feedback
Nebius Token Factory
PatchScout uses Nebius Token Factory’s OpenAI-compatible chat completions API to run NVIDIA Nemotron 3 Super 120B A12B for dependency-migration diagnosis and structured code-edit generation. The API interface let us integrate hosted inference into our Next.js/TypeScript application without managing model-serving infrastructure.
Our zero-to-hello-world integration path was configuring the API key, endpoint, and model identifier, then making a live inference request. Moving from that first response to an executable patch required additional application work: supplying real repository context, requesting structured JSON, validating edits, and handling retries. We did not record onboarding time, so we cannot provide a measured time-to-first-response.
We would welcome an end-to-end coding-agent example that covers these steps together, including unusable outputs and executable verification. We would use Token Factory again for hosted inference because it fits our existing application stack and lets us focus on the agent workflow. We did not independently deploy workloads on Nebius AI Cloud, so we cannot assess that service from firsthand use.
Token Factory Sandboxes / ConTree
We used the official contree-client JavaScript SDK to execute repository tests in isolated, branchable sandbox checkpoints. This provided the strongest evidence in PatchScout: on our public Express 5 fixture, the baseline npm test exited 1; after editing src/app.js, the same command exited 0. Checkpoints also supported reversible patch attempts and reuse of a clean dependency-installed environment during bounded repair.
The practical onboarding path was connecting the SDK with sandbox access, executing the baseline, applying a candidate edit, and checking the resulting test exit code. The important integration challenge was long-running execution: sandbox and live-agent runs could exceed one minute, so we raised our application route limit from 60 to 300 seconds. This was an orchestration constraint, not evidence of a sandbox service failure.
A documented reference workflow for durable jobs, polling, stage timeouts, and checkpoint recovery would help developers move beyond a synchronous request. We would use Sandboxes/ConTree again because isolated execution and reversible checkpoints make patch verification credible.
NVIDIA Nemotron
We used nvidia/nemotron-3-super-120b-a12b through Token Factory to reason over the incident, repository context, and current upstream documentation retrieved with Tavily, then propose minimal path/search/replace edits. In the verified Express 5 case, the workflow produced a route edit that passed the original failing test.
Our onboarding used hosted inference rather than a local model deployment. The main challenge appeared after basic inference worked: Nemotron occasionally returned no usable edits. We mitigated this with structured JSON output, explicit repository context, retries on empty edit plans, and a bounded repair pass informed by real test output.
More reliable actionable edit output—and clearer differentiation between “no change needed” and “unable to produce a patch”—would improve this use case. We would continue evaluating Nemotron for source-grounded coding workflows, while retaining executable tests as the acceptance criterion. Our current evidence demonstrates one migration fixture, not broad reliability across arbitrary repositories.
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