Self-host Devstral 2 on dedicated GPU clusters
Run Mistral's frontier code-agent model on bare-metal Kubernetes in EU data centers. Turn support-style integration requests into grounded engineering handoffs without moving prompts, snippets, or credentials outside your infrastructure.
No model/quant candidates pass the quality filter.
Translate support context into something engineering can ship
Use the suggested prompts or write your own. Devstral keeps the handoff intentionally compact: ticket, explanation, and code.
Playground
Support request in. Engineering ticket out.
ID: devstral-2512Describe the integration problem. Devstral turns it into a concise ticket, a short reasoning note, and a Python starter you can hand to an engineer.
Suggested requests
Derived from Asergo’s GraphQL docs and common support-style integration asks.
Custom request
0/1500 characters
Generated output
Engineering ticket, short explanation, and Python starter implementation.
Use Cases
Turn support into engineering tickets
Support threads, logs, and API notes rarely arrive in a form engineering can ship. Devstral turns the escalation into a ticket package with repro steps, acceptance criteria, and a code starter so the handoff does not depend on someone rewriting the case by hand.
Keep internal API schemas, credentials, and escalation history inside the same boundary. Enforce a fixed output schema before anything is posted into backlog tools.
Dependencies into upgrade plans
Lockfiles, changelogs, and failing jobs only become useful when someone turns them into sequenced work. Devstral can map recurring upgrade pressure into ordered tasks with risk notes, test scope, and rollback-aware checks for the engineering team.
Best run as a scheduled internal workload against mirrored repositories. The model proposes the work, but merge approval and execution stay with engineering.
Code and engineering copilots behind the boundary
Engineers often need grounded answers that span repository code, CI traces, and internal runbooks. Devstral can sit behind the boundary and return code-aware guidance, patch outlines, and next commands without exposing source or operational context to an external service.
Scope retrieval to approved repositories and runbooks only. Every answer should cite the files or docs it used so engineers can verify before acting.
Workload fit
Not sure this model fits your use case?
The private LLM study maps 29 workloads across six patterns and shows where each model family fits.
Infrastructure
Looking at the GPU and deployment side?
GPU provider options, deployment architecture, and how we manage the serving layer on Kubernetes.